阅读说明：本技术 确定目标任务的方法、装置、电子设备及存储介质 (Method and device for determining target task, electronic equipment and storage medium ) 是由 李强 于 2020-10-16 设计创作，主要内容包括：本发明实施例提供了一种确定目标任务的方法、装置、电子设备及存储介质,该方法包括：对各待发送任务,确定当前待发送任务的任务属性信息,根据所述任务属性信息,确定所述当前待发送任务与目标用户之间的匹配度；其中,所述任务属性信息中包括所述当前待发送任务对应的待发送文本内容、所述当前待发送任务对应的任务创建者标识以及所述当前待发送任务对应的任务物品品类中的至少一个；根据各待发送任务与目标用户之间的匹配度,从各待发送任务中确定与目标用户相对应的目标任务；将所述目标任务对应的待发送文本内容发送至所述目标用户的终端设备。本技术方案,提高了确定出的目标任务与目标用户之间的匹配度,从而提高了任务转化率的效果。(The embodiment of the invention provides a method, a device, electronic equipment and a storage medium for determining a target task, wherein the method comprises the following steps: for each task to be sent, determining task attribute information of the current task to be sent, and determining the matching degree between the current task to be sent and a target user according to the task attribute information; the task attribute information comprises at least one of text content to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent and a task article class corresponding to the current task to be sent; determining a target task corresponding to a target user from each task to be sent according to the matching degree between each task to be sent and the target user; and sending the text content to be sent corresponding to the target task to the terminal equipment of the target user. According to the technical scheme, the matching degree between the determined target task and the target user is improved, and therefore the effect of the task conversion rate is improved.)

1. A method of determining a target task, comprising:

for each task to be sent, determining task attribute information of the current task to be sent, and determining the matching degree between the current task to be sent and a target user according to the task attribute information; the task attribute information comprises at least one of text content to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent and a task article class corresponding to the current task to be sent;

determining a target task corresponding to a target user from each task to be sent according to the matching degree between each task to be sent and the target user;

and sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

2. The method according to claim 1, before determining a matching degree between the current task to be sent and a target user according to the task attribute information, further comprising:

acquiring a sent task and a total sending frequency within a preset time length, and clicking an effective task and a total effective clicking frequency of the sent task; generating a sample set based on the sent tasks, the total sending times, the effective tasks and the total effective click times;

processing first text content of a current sent task based on a word segmentation tool, a preset disabled word and a preset phrase model aiming at each sent task in a sample set, and determining a related word of the current sent task; generating a related vocabulary set according to the related vocabulary of each sent task;

determining the sending times and the effective clicking times of the vocabulary of at least one sent task to which the current associated vocabulary belongs aiming at each associated vocabulary in the associated vocabulary set, determining the heat value of the current associated vocabulary according to the sending times and the total sending times of the vocabulary, and determining the effective trigger value of the current associated vocabulary according to the effective clicking times and the total effective clicking times; determining a total trigger value of the triggered content tasks with the preset duration according to the total effective clicking times and the total sending times;

and correspondingly storing each associated vocabulary, and the heat value, the effective trigger value and the total trigger value corresponding to the associated vocabulary to a preset position so as to determine the matching degree between the task to be sent and the target user according to the heat value, the effective trigger value and the total trigger value of each vocabulary in the text content to be sent.

3. The method according to claim 2, wherein the processing the first text content of the currently sent task based on the word segmentation tool, the preset disabled vocabulary and the preset phrase model, and the determining the associated vocabulary of the currently sent task comprises:

dividing the first text content into at least one vocabulary to be processed based on a word segmentation tool; removing the vocabulary which is the same as the preset disabled vocabulary from the at least one vocabulary to be processed to obtain at least one vocabulary to be used;

combining the at least one vocabulary to be used into at least one phrase to be used based on the preset phrase model and the position information of the at least one vocabulary to be used in the first text content;

and determining the associated vocabulary of the current task to be sent based on the at least one vocabulary to be used and the at least one phrase to be used.

4. The method according to claim 3, wherein the combining the at least one vocabulary to be used into at least one phrase to be used based on the preset phrase model and the position information of the at least one vocabulary to be used in the first text content comprises:

combining two adjacent vocabularies to be used of the position information into a phrase to be processed based on a preset phrase model;

and if the phrase to be processed is consistent with part of the content in the first text content, taking the phrase to be processed as a phrase to be used.

5. The method according to claim 2, wherein the task attribute information includes text content to be sent, and the determining the matching degree between the current task to be sent and a target user according to the task attribute information includes:

determining at least one target associated vocabulary corresponding to the text content to be sent;

for each target associated vocabulary, calling a heat value and an effective trigger value corresponding to the current target associated vocabulary from the preset position;

and determining the matching degree between the current task to be sent and the target user according to the heat value, the effective trigger value and the total trigger value of each target associated vocabulary.

6. The method according to claim 5, wherein the determining the matching degree between the task to be sent and the target user according to the heat value, the effective trigger value and the total trigger value of each target associated vocabulary comprises:

determining a first intermediate processing value corresponding to the current task to be sent according to the effective trigger value and the total trigger value of each target associated vocabulary; determining a second intermediate processing value of the current task to be sent according to the heat value of each target associated vocabulary;

and determining the matching degree between the current task to be sent and the target user based on the first intermediate processing value and the second intermediate processing value.

7. The method according to claim 2, wherein the task attribute information includes text content to be sent, and the determining the matching degree between the current task to be sent and a target user according to the task attribute information includes:

determining target feature words included in the text to be sent according to each feature word in a feature word library;

determining the characteristic evaluation value of each target characteristic vocabulary according to the corresponding relation between the characteristic vocabulary and the characteristic vocabulary evaluation value established in advance;

and determining the matching degree between the current task to be sent and the target user according to the characteristic evaluation value.

8. The method of claim 7, further comprising: establishing a corresponding relation between the characteristic words and the characteristic word evaluation values;

the establishing of the correspondence between the feature vocabulary and the feature vocabulary evaluation value includes:

for each effective task, extracting a feature vocabulary corresponding to the current effective task from a second text corresponding to the current effective task according to a preset rule template, and forming a feature vocabulary library according to the feature vocabulary of each effective task;

according to each feature vocabulary, obtaining a feature vocabulary evaluation value of the current feature vocabulary based on the effective click times and the total effective click times corresponding to the current feature vocabulary;

a correspondence relationship between each of the feature words and the corresponding feature word evaluation value is established to determine a feature evaluation value corresponding to the target feature word based on the correspondence relationship.

9. The method according to claim 1, wherein the task attribute information includes a task creator identifier corresponding to a current task to be sent, and the determining a matching degree between the current task to be sent and a target user according to the task attribute information includes:

determining a creator task conversion value corresponding to the task creator identification according to a mapping relation between a pre-established task creator identification and a creator task conversion value, and determining the matching degree between the current task to be sent and the target user based on the creator task conversion value.

10. The method of claim 9, further comprising: establishing a mapping relation between a task creator identifier and a creator task conversion value;

the establishing of the mapping relationship between the task creator identification and the creator task conversion value comprises the following steps:

aiming at each creator identification, determining the number of creating tasks and creating tasks corresponding to the current creator identification from the sent tasks within a preset time length;

aiming at each created task, determining the task click rate of the current created task according to the task click quantity corresponding to the current created task and the created task sending times of the current created task;

determining a creator task conversion value of the current creator identification according to the task click rate of each creation task and the number of the creation tasks;

and establishing a mapping relation between the creator identification and the creator task conversion value, so as to obtain the creator task conversion value corresponding to the creator identification from the mapping relation according to the creator identification to which the current task to be sent belongs.

11. The method according to claim 1, wherein the task attribute information includes a task item class corresponding to the current task to be sent, and the determining the matching degree between the current task to be sent and a target user according to the task attribute information includes:

acquiring a target article type associated with the target user, and determining a type association matching value according to the target article type and the task article type;

determining a class association coefficient value according to the number of the task categories of the task item classes and the number of the target categories of the target item classes in the task item classes;

and determining the matching degree between the current task to be sent and the target user according to the class association matching value and the class association coefficient value.

12. The method of claim 11, wherein determining a class association match value based on the target item class and the task item class comprises:

determining a task three-level category included in the task item category and a target three-level category corresponding to the target item category;

determining a target tertiary category included in the task tertiary category to obtain a matched tertiary category;

and respectively determining a matching value corresponding to each matching tertiary category, and taking the maximum matching value as the associated matching value of the category.

13. The method according to claim 1, wherein the determining a matching degree between the current task to be sent and a target user according to the task attribute information comprises:

and determining the matching degree between the current task to be sent and the target user according to the matching degree corresponding to at least one task attribute information.

14. The method according to claim 13, wherein the determining the matching degree between the current task to be sent and the target user according to the matching degree corresponding to at least one task attribute information comprises:

and determining the matching degree between the current task to be sent and the target user according to the weight value and the matching degree corresponding to each task attribute information.

15. The method according to claim 1, wherein the determining a target task corresponding to a target user from among the tasks to be sent according to the matching degree between each task to be sent and the target user comprises:

and determining the task to be sent corresponding to the highest matching degree according to the matching degree between each task to be sent and the target user, and taking the task to be sent as the target task corresponding to the target user.

16. An apparatus for determining a target task, comprising:

the matching degree determining module is used for determining task attribute information of a current task to be sent for each task to be sent and determining the matching degree between the current task to be sent and a target user according to the task attribute information; the task attribute information comprises at least one of text content to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent and a task article class corresponding to the current task to be sent;

the target task determining module is used for determining a target task corresponding to a target user from each task to be sent according to the matching degree between each task to be sent and the target user;

and the target task sending module is used for sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

17. An electronic device, characterized in that the electronic device comprises:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement a method for determining a target task as recited in any of claims 1-15.

18. A storage medium containing computer-executable instructions for performing a method of determining a target task as recited in any one of claims 1-15 when executed by a computer processor.

Technical Field

The embodiment of the invention relates to the technical field of computers, in particular to a method and a device for determining a target text, electronic equipment and a storage medium.

Background

With the increasing development of electronic commerce, in order to improve the marketing effect, a short message sending mode is mostly adopted to realize a marketing mode reaching the user.

Currently, the main steps of sending short messages to each user are: the operators select the user groups in circles in different modes and send corresponding short messages to the selected users. In this way, there is a situation that a certain user has multiple short message tasks to be sent within a certain time length range.

The technical problem of poor user experience caused by frequent short message sending tasks to the target user within a certain time is solved. Generally, only one short message task can be sent to a target user within a certain time, the short message task sent to the target user is particularly important, and the target short message task is mainly determined according to the time sequence of receiving the short message tasks at present, namely, the earliest received short message task is taken as the target short message task.

In the process of implementing the invention, the inventor finds that the prior art has the following problems:

when the short message tasks are sent to the corresponding users based on the sequence of the received short message tasks, the matching degree between the sent short message tasks and the users is low, and therefore the users cannot trigger the short message tasks, and the technical problem that the conversion rate of the short message tasks is low is caused.

Disclosure of Invention

The invention provides a method, a device, electronic equipment and a storage medium for determining a target task, which are used for determining the target task with the best matching degree with a target user from all tasks to be sent, so that the technical effect of improving the conversion rate of the target task is achieved.

In a first aspect, an embodiment of the present invention provides a method for determining a target task, where the method includes:

for each task to be sent, determining task attribute information of the current task to be sent, and determining the matching degree between the current task to be sent and a target user according to the task attribute information; the task attribute information comprises at least one of text content to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent and a task article class corresponding to the current task to be sent;

determining a target task corresponding to a target user from each task to be sent according to the matching degree between each task to be sent and the target user;

and sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

In a second aspect, an embodiment of the present invention further provides an apparatus for determining a target task, where the apparatus includes:

the matching degree determining module is used for determining task attribute information of a current task to be sent for each task to be sent and determining the matching degree between the current task to be sent and a target user according to the task attribute information; the task attribute information comprises at least one of text content to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent and a task article class corresponding to the current task to be sent;

the target task determining module is used for determining a target task corresponding to a target user from each task to be sent according to the matching degree between each task to be sent and the target user;

and the target task sending module is used for sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement a method for determining a target task as in any of the embodiments of the invention.

In a fourth aspect, embodiments of the present invention also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are used to perform the method for determining a target task according to any one of the embodiments of the present invention.

According to the technical scheme of the embodiment of the invention, the matching degree between each task to be sent and the target user can be determined by processing the task attribute information of each task to be sent, so that the target task is determined from each task to be sent based on the matching degree, the matching degree between the determined target task and the target user is improved, and then the target task can be sent to the terminal corresponding to the target user after the target task is determined.

Drawings

In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.

Fig. 1 is a flowchart illustrating a method for determining a target task according to an embodiment of the present invention;

fig. 2 is a flowchart illustrating a method for determining a target task according to a second embodiment of the present invention;

fig. 3 is a flowchart illustrating a method for determining a target task according to a second embodiment of the present invention;

fig. 4 is a flowchart illustrating a method for determining a target task according to a third embodiment of the present invention;

fig. 5 is a flowchart illustrating a method for determining a target task according to a third embodiment of the present invention;

fig. 6 is a flowchart illustrating a method for determining a target task according to a fourth embodiment of the present invention;

fig. 7 is a flowchart illustrating a method for determining a target task according to a fifth embodiment of the present invention;

fig. 8 is a flowchart illustrating a method for determining a target task according to a sixth embodiment of the present invention;

fig. 9 is a schematic structural diagram of an apparatus for determining a target task according to a seventh embodiment of the present invention;

fig. 10 is a schematic structural diagram of an electronic device according to an eighth embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.

Example one

Fig. 1 is a flowchart illustrating a method for determining a target task according to an embodiment of the present invention, where this embodiment is suitable for a situation where multiple tasks to be sent exist for a same target user, a matching degree between each task to be sent and the target user may be respectively determined, so as to determine a target task from all tasks to be sent according to the matching degree, and send the target task to a terminal device to which the target user belongs.

As shown in fig. 1, the method of this embodiment includes:

s110, for each task to be sent, determining task attribute information of the current task to be sent, and determining the matching degree between the current task to be sent and a target user according to the task attribute information.

In this embodiment, the task to be sent may be a short message task. Namely, the task to be sent refers to a short message task which needs to be sent to a target user. Because only one short message task can be sent to the user within the preset time, but the number of the tasks to be sent actually corresponding to the user is multiple, in order to improve the task conversion rate and achieve the marketing purpose, the target task with the best matching degree with the target user can be determined from all the tasks to be sent, and the target task is sent to the target user. The matching degree between the task to be sent and the target user is determined, and the matching degree can be determined based on the task attribute information of the task to be sent. The matching degree is used for representing the degree of engagement between the task to be sent and the target user, optionally, the higher the matching degree is, the better the degree of engagement between the task to be sent and the user is, correspondingly, the higher the probability that the user triggers the task to be sent is, and the higher the conversion rate of the task is.

It should be noted that the matching degree between each task to be sent and the target user can be determined in the same manner, and this embodiment is described by taking one task to be sent as an example.

The task attribute information comprises at least one of text content to be sent corresponding to the task to be sent, a task creator identifier corresponding to the task to be sent and a task item class corresponding to the task to be sent.

The text content to be sent may be short message content. The task creator can create the short message task, and the task creator identification is the user identification for creating the short message task. When the short message task is created, the article type corresponding to the short message task can be determined or set, and the article type corresponding to the short message task can be used as the task article type. The task attribute information may include at least one of the above information, and if the task attribute information includes one, the corresponding task attribute information may be processed to obtain a matching degree between the task to be sent and the target user. If the task attribute information comprises a plurality of pieces of information, each piece of task attribute information can be processed respectively, and after the matching degree is obtained, all the matching degrees can be integrated to obtain the matching degree between the task to be sent and the target user.

Specifically, for each task to be sent, task attribute information of each task to be sent can be determined, and by processing each task attribute information, the matching degree between the task to be sent and the target user can be determined.

And S120, determining a target task corresponding to the target user from each task to be sent according to the matching degree between each task to be sent and the target user.

The matching degree is used for representing the degree of engagement between the task to be sent and the target user, and optionally, the higher the matching degree is, the higher the degree of engagement between the user and the task to be sent is, that is, the higher the probability that the user triggers the task to be sent corresponding to the matching degree is, the higher the task conversion efficiency of the task to be sent is correspondingly. Therefore, the target task can be determined based on the matching degree between each task to be sent and the target user.

Specifically, after the matching degree between each task to be sent and the target user is determined, the task to be sent corresponding to the task with the highest matching degree can be obtained, and the task to be sent is used as the target task.

It should be noted that after the target task is determined, if the number of the tasks to be sent is increased, optionally, the tasks to be sent are newly added, the method provided by this embodiment may be adopted to determine the matching degree between each newly added task to be sent and the user, and then the target task is determined based on the matching degree of the newly added task to be sent and the matching degree of the original task to be sent.

And S130, transmitting the text content to be transmitted corresponding to the target task to the terminal equipment of the target user.

Specifically, after the target task is determined, the target task may be sent to the terminal device corresponding to the target user. Because the target task is a short message task, the text content to be sent corresponding to the target task is mainly sent to the terminal equipment corresponding to the target user. The target user can trigger the short message task received by the terminal equipment, and when the target user triggers the short message task, the conversion rate of the short message task can be improved.

According to the technical scheme of the embodiment of the invention, the matching degree between each task to be sent and the target user can be determined by processing the task attribute information of each task to be sent, so that the target task is determined from each task to be sent based on the matching degree, the matching degree between the determined target task and the target user is improved, and then the target task can be sent to the terminal corresponding to the target user after the target task is determined.

Example two

Fig. 2 is a flowchart illustrating a method for determining a target task according to a second embodiment of the present invention. On the basis of the foregoing embodiment, if the task attribute information includes the text content to be sent corresponding to the current task to be sent, the specific implementation manner of determining the matching degree between the current task to be sent and the target user according to the task attribute information in S110 may be referred to in this embodiment. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein.

Before determining the matching degree between the task to be sent and the target user according to the text content to be sent, the associated vocabulary included in each task, and the heat value and the effective trigger value corresponding to each associated vocabulary may be determined according to a task set including a plurality of tasks, which is obtained in advance, so that when the text content of the task to be sent is processed, the matching degree between the task to be sent and the target user may be determined based on the heat value and the effective trigger value, which are determined in advance.

Optionally, the sent task and the total sending times within a preset time length are obtained, and the effective task and the total effective clicking times of the sent task are clicked; generating a sample set based on the sent tasks, the total sending times, the effective tasks and the total effective click times; processing the first text content of the current sent task based on the word segmentation tool, the preset disabled words and the preset phrase model aiming at each sent task in the sample set, and determining the associated words of the current sent task; generating a related vocabulary set according to the related vocabulary of each sent task; determining the sending times and the effective clicking times of the vocabulary of at least one sent task to which the current associated vocabulary belongs aiming at each associated vocabulary in the associated vocabulary set, determining the heat value of the current associated vocabulary according to the sending times and the total sending times of the vocabulary, and determining the effective trigger value of the current associated vocabulary according to the effective clicking times and the total clicking times; determining a total trigger value of the current associated vocabulary according to the total number of effective clicks and the total number of sending times; and correspondingly storing each associated vocabulary, and the heat value, the effective trigger value and the total trigger value corresponding to the associated vocabulary to a preset position so as to determine the matching degree between the task to be sent and the target user according to the stored heat value, effective trigger value and total trigger value.

The preset duration can be three months, one year and the like, and the operation and maintenance personnel can set the specific duration of the preset duration according to actual requirements. And taking the tasks sent within the preset time length as a task set. The sent task refers to a task which is created by a task creator and sent to a corresponding user within a preset time length. The task sending times of each sent task can be determined, and the total sending times of the sent tasks can be obtained by accumulating the task sending times of each task. After the task is sent to the terminal corresponding to the user, the user can trigger the task, the task triggered by the user is used as an effective task, correspondingly, the number of times that the task is triggered in the sent task can be determined, and the number of times that the task is triggered can be used as the total number of effective clicks. According to the sent tasks, the total sending times, the effective tasks and the total effective click times, a sample set can be generated. The word segmentation tool can be a word segmentation source-opening component, can be selected, can be used for word segmentation, and the like, the specific word segmentation tool is not limited, and a user can set the word segmentation tool according to actual requirements as long as the word segmentation can be realized. The preset disabled words can be preset disabled words, and words without practical meaning in the text content to be sent can be removed based on the preset disabled words, and optionally, "yes", and the like. The preset phrase model is a model combining two vocabularies into phrases. The associated words are words and/or phrases obtained after the first text content is processed. Each sent task has associated vocabulary corresponding to the sent task, and an associated vocabulary set comprising all associated vocabularies can be generated according to the associated vocabulary corresponding to each sent task. The heat value may characterize the frequency of occurrence of each associated word, and the valid trigger value may characterize the probability that a text may be clicked when the word appears in the text. The total trigger value is the probability value of the clicked task with the preset duration.

In this embodiment, the processing the first text content of the currently sent task based on the word segmentation tool, the preset disabled vocabulary and the preset phrase model, and determining the associated vocabulary of the currently sent task includes: dividing the first text content into at least one vocabulary to be processed based on a word segmentation tool; removing the vocabulary which is the same as the preset disabled vocabulary from the at least one vocabulary to be processed to obtain at least one vocabulary to be used; combining the at least one vocabulary to be used into at least one phrase to be used based on the preset phrase model and the position information of the at least one vocabulary to be used in the first text content; and determining the associated vocabulary of the current task to be sent based on the at least one vocabulary to be used and the at least one phrase to be used.

The word segmentation tool can be any tool capable of realizing word segmentation processing on the text content. The first text content may be divided into a plurality of words to be processed based on the segmentation tool. In order to improve the effectiveness of the vocabulary to be processed, the vocabulary same as the preset disabled vocabulary can be removed, for example, the vocabulary to be processed comprises ' the ' vocabulary ', the preset vocabulary also comprises ' the ' vocabulary ', and the ' vocabulary can be deleted. The vocabulary to be used is the vocabulary obtained after the vocabulary to be processed is processed based on the preset disabled vocabulary. The preset phrase model may be a model constructed in a bigram-like manner, and the word to be used may be constructed based on the preset phrase model to obtain at least one phrase to be used. According to the vocabulary to be used and the phrase to be used, the associated vocabulary corresponding to the currently sent task can be determined, namely the associated vocabulary comprises the vocabulary to be used and the phrase to be used.

In this embodiment, the word to be used is constructed based on the preset word group model to obtain the word group to be used, which may be: combining two adjacent vocabularies to be used of the position information into a phrase to be processed based on a preset phrase model; and if the phrase to be processed is consistent with part of the content in the first text content, taking the phrase to be processed as a phrase to be used.

Wherein the position information may be a position of the vocabulary to be used in the first text content. The adjacent position information can also be understood as two adjacent vocabularies to be used after word segmentation.

Specifically, based on the preset phrase model, two adjacent vocabularies to be used of the position information can be combined/spliced into a phrase to be used. After the phrase to be used is obtained, whether a vocabulary consistent with the phrase to be used exists in the first text content can be judged, if yes, the vocabulary is reserved, if not, the phrase to be used can be deleted, and the reason set in the way is as follows: the phenomenon that the filtering of stop words and the like causes the splicing of actual non-adjacent word segmentation results into word groups is avoided.

Specifically, the sent tasks sent to the user based on the system and the total sending times corresponding to all the sent tasks are obtained within one year, and meanwhile, the triggering times of the user on all the sent tasks, namely the effective total clicking times, are determined. Aiming at each sent task, first text content corresponding to the current sent task can be obtained, and the first text content is divided into a plurality of words to be processed through a word segmentation tool; based on the preset disabled vocabulary, deleting the preset disabled vocabulary in the plurality of vocabularies to be processed, and taking the rest vocabularies to be processed as vocabularies to be used. And splicing two adjacent words to be used into a phrase to be processed based on a preset phrase model, taking the phrase to be processed as the phrase to be used when the phrase which is the same as the phrase to be processed exists in the first text content, and correspondingly deleting the phrase to be processed if the phrase which is the same as the phrase to be processed does not exist in the first text content. The vocabulary to be used and the phrase to be used of each sent task can be used as the associated vocabulary, and the associated vocabulary set can be generated based on the associated vocabulary of each sent task. For each associated vocabulary in the associated vocabulary combination, determining the heat value of the associated vocabulary according to the transmitting times of the vocabulary of the transmitted task to which the associated vocabulary belongs and the total transmitting times of all tasks; and determining the effective trigger value of the current associated vocabulary according to the effective click times and the total effective click times of the sent tasks to which the associated vocabulary belongs. The associated vocabulary, the heat value corresponding to the associated vocabulary and the effective trigger value can be correspondingly stored to a preset storage position, so that when the task attribute information includes the text content to be sent, the target associated vocabulary included in the text content can be determined, the heat value corresponding to the target associated vocabulary and the effective trigger value are called, and the matching degree between the task to be sent and the target user is determined.

That is to say, the implementation can determine the heat value and the effective trigger value of the associated vocabulary included in all the task information by processing the task information sent within the preset time in advance, and can determine the matching degree between each task to be sent and the target user based on the associated value and the effective trigger value, thereby improving the technical effects of convenience and high efficiency of determining the matching degree.

On the basis of the technical scheme, after the heat value and the effective trigger value of each associated vocabulary are determined, the matching degree between the task to be sent and the target user can be determined according to the predetermined heat value and the predetermined effective trigger value.

As shown in fig. 2, the method includes:

s210, determining at least one target associated vocabulary corresponding to the text content to be sent.

Because the tasks to be sent are short message tasks, each task to be sent has a text corresponding to the task to be sent, and the text can be used as the text content to be sent. The text to be sent can be divided into a plurality of vocabularies based on the word segmentation tool, and the vocabularies without actual meanings in the plurality of vocabularies are deleted, optionally deleted, tweed and other vocabularies, so that the target vocabularies to be used are obtained. And combining adjacent target words to be used into target phrases to be processed based on the preset phrase model. And detecting whether the text content to be sent comprises a target phrase to be processed, if so, taking the target phrase to be processed as the target phrase to be used, and if not, deleting the target phrase to be processed. And determining a target associated vocabulary of the text content to be sent based on the target vocabulary to be used and the target phrase to be used.

S220, aiming at each target associated vocabulary, calling a heat value and an effective trigger value corresponding to the current target associated vocabulary from the preset position.

Wherein, the number of the target associated vocabulary can be one or more. A heat value and a valid trigger value for each target associated vocabulary may be determined separately. The predetermined location may be understood as a storage location where the associated vocabulary, the heat value corresponding to the associated vocabulary, and the valid trigger value are stored. The heat value and valid trigger value corresponding to the associated vocabulary are predetermined,

specifically, for each target related vocabulary, the heat value and the valid trigger value corresponding to the current target related vocabulary may be retrieved from the preset positions. Namely, the hot value and the effective trigger value corresponding to each target vocabulary to be used and the target phrase to be used are called from the preset position.

S230, determining the matching degree between the current task to be sent and the target user according to the heat value, the effective trigger value and the total trigger value of each target associated vocabulary.

Specifically, after the heat value and the effective trigger value of each target associated vocabulary are determined, the matching degree between the current task to be sent and the target user can be determined according to the heat values, the effective trigger values and the total trigger values of all the target associated vocabularies.

Optionally, determining a first intermediate processing value corresponding to the current task to be sent according to the effective trigger value and the total trigger value of each target associated vocabulary; determining a second intermediate processing value of the current task to be sent according to the heat value of each target associated vocabulary; and determining the matching degree between the current task to be sent and the target user based on the first intermediate processing value and the second intermediate processing value.

The first intermediate processing value is determined based on the effective trigger value and the total trigger value of each target associated vocabulary, and optionally, the first intermediate processing value is determined according to the product of the effective trigger value and the total trigger value of each target associated vocabulary. The second intermediate processing value is determined according to the heat value of each target related vocabulary, and optionally, the second intermediate processing value is determined based on the product of the heat values of each target related vocabulary. The degree of matching may be determined based on a ratio of the first intermediate processed value to the second intermediate processed value.

In this embodiment, if the task attribute information includes text content to be sent corresponding to the current task to be sent, the matching degree between the current task to be sent and the target user may be determined in the above manner. The other tasks to be sent can determine the matching degree between the tasks and the target user in the same way.

And S240, determining a target task corresponding to the target user from each task to be sent according to the matching degree between each task to be sent and the target user.

And S250, transmitting the text content to be transmitted corresponding to the target task to the terminal equipment of the target user.

According to the technical scheme of the embodiment of the invention, the engagement degree between the task to be sent and the target user can be determined by processing the text content to be sent of the task to be sent, so that the task to be sent with the highest engagement degree is sent to the target user, the matching degree between the target user and the target task is improved, and the technical effects of the probability of triggering the target task by the user and the task conversion rate are improved.

As an alternative embodiment of the foregoing embodiment, fig. 3 is a flowchart illustrating a method for determining a target task according to a second embodiment of the present invention. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein.

As shown in fig. 3, the method further comprises:

and S310, starting.

It can be understood as starting to determine the matching degree between the task to be sent and the target user.

And S320, performing word segmentation processing on the short message text by adopting ANSJ.

The ANJS can be understood as an open source word segmentation tool, and word segmentation processing can be performed on the short message text based on the open source word segmentation tool and the stop words in the preset stop word bank. The short message text can be understood as the first text content corresponding to the sent task.

Specifically, the short message text is processed based on the ANJS, at least one vocabulary to be processed corresponding to the short message text can be determined, stop words in the vocabulary to be processed are removed based on stop words in a preset stop word bank, and the remaining vocabulary to be processed is the vocabulary to be used, so that a word segmentation result corresponding to the short message text is obtained.

S330, constructing a phrase by using a bigram mode.

Specifically, according to the word segmentation result, a word group construction can be performed in a bigram mode similar to the bigram mode, for example, the first text content is 'house i like the house type', the word segmentation result obtained based on the ANJS word segmentation tool and the preset stop vocabulary includes 'like, house type and house'. Two adjacent vocabularies can be spliced together by using a bigram mode, and the constructed phrase comprises 'favorite house type and house type house'. Whether the first text content includes the constructed phrase or not can be judged, if yes, the phrase can be reserved, and otherwise, the phrase is deleted. The first text content does not include the favorite house type and the house type house, so that the phrase to be used corresponding to the first text content does not exist. The vocabulary to be used corresponding to the first text content is "like, house type, house", i.e. the associated vocabulary is "like, house type, house".

And S340, counting the heat value and the effective trigger value of each vocabulary and phrase.

The statistics of the heat value and the effective trigger value of each word and phrase can be to acquire historical short message task sending data and click data of one year, and to calculate the heat value and the effective trigger value of each word to be used and each phrase to be used in each short message task, namely the heat value and the effective trigger value of the associated word corresponding to each short message task. Wherein, the hot value can be understood as the occurrence frequency of the associated vocabulary, and the effective trigger value can be understood as the frequency of the triggered tasks including the effective vocabulary.

Based on S330, the associated vocabulary corresponding to each sent task may be determined, and the associated vocabulary includes the vocabulary to be used and the phrase to be used. After determining the associated vocabulary corresponding to each sent task, the heat value and the effective trigger value corresponding to each associated vocabulary can be determined,

for example, for each associated vocabulary, the sending times a of the sent tasks to which the current associated vocabulary belongs may be determined, and the heat value P (associated vocabulary) of the current associated vocabulary may be determined according to the ratio of the sending times a to the total sending times B of all the sent tasks. Determining the clicked times D and the total effective clicked times E of the sent tasks to which the current associated vocabulary belongs, and determining the effective trigger value P (associated vocabulary/trigger) of the current associated vocabulary according to the ratio of the clicked times D and the total effective clicked times E of the tasks. From the total number of valid clicks and the total number of transmissions, a total trigger value P (total) may be determined. And respectively determining the heat value and the effective trigger value of each associated vocabulary by adopting the mode.

After the heat value and the effective trigger value of each associated vocabulary are determined, the corresponding relation among the associated vocabulary, the heat value and the effective trigger value can be established and stored to a preset position, so that when the task attribute information comprises the text content to be sent, the matching degree between the text content to be sent and the target user is determined based on the corresponding relation stored in the preset position, and the target task corresponding to the target user is further determined.

And S350, aiming at the current task to be sent, determining the matching degree between the current text to be sent and the target user according to the heat value and the effective trigger value corresponding to the current task to be sent.

Specifically, the text content to be sent of the current task to be sent can be obtained, and target associated words included in the text content to be sent are determined to be A, B, C, D respectively based on the word segmentation tool. Based on the heat value and the effective trigger value corresponding to each associated vocabulary stored in the preset position, the heat value of the target associated vocabulary can be respectively determined, namely, the occurrence probability values are P (A), P (B), P (C) and P (D), and the effective trigger values of the associated vocabulary are P (A \ trigger), P (B \ trigger) and P (C \ trigger) P (D \ trigger).

Based on the formula P [ P (a \ trigger) × P (B \ trigger) × P (C \ trigger) × P (D \ trigger) ×/[ P (a) × P (B) × P (C) × P (D) ] ], the degree of matching between the current task to be issued and the target user can be determined. S340 may be repeatedly performed to determine the matching degree between each task to be sent and the target user.

It should be noted that, since the matching degree at this time is determined based on the content of the text to be sent, the matching degree obtained at this time can be understood as the quality value of the short message text.

And S360, determining a target task from the tasks to be sent according to the matching degree, and sending the target task to the terminal equipment corresponding to the target user.

After the matching degree between each task to be sent and the target user is determined, the target task can be determined from all the tasks to be sent according to the matching degree, and the target task is sent to the terminal device corresponding to the target user.

It should be noted that, if the task attribute information only includes text content to be sent corresponding to a task to be sent, a target task corresponding to a target user may be directly determined based on the matching degree.

According to the technical scheme of the embodiment of the invention, the matching degree between the text content to be sent and the target user can be determined by processing the text content to be sent of each task to be sent, so that the target task is determined from all the tasks to be sent based on the matching degree, the matching degree between the determined target task and the user is improved, and the technical effect of the task conversion rate is improved.

EXAMPLE III

Fig. 4 is a flowchart illustrating a method for determining a target task according to a third embodiment of the present invention. On the basis of the foregoing embodiment, the text content to be sent may further include preferential vocabulary information, and if the text content to be sent includes preset preferential vocabulary information, the matching degree may be updated on the basis of determining the matching degree between the task to be sent and the user according to the text content to be sent. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein.

As shown in fig. 4, the method includes:

and S410, determining task attribute information of the current task to be sent for each task to be sent.

And S420, determining a target feature vocabulary included in the text to be sent according to the text content to be sent included in the task attribute information and according to each feature vocabulary in the feature vocabulary library.

Wherein, each characteristic vocabulary in the characteristic vocabulary library is preset. The feature vocabulary included in the text content to be sent can be determined according to each feature vocabulary included in the feature vocabulary library, and the feature vocabulary included in the text content to be sent is used as the target feature vocabulary.

S430, determining the characteristic evaluation value of each target characteristic vocabulary according to the corresponding relation between the characteristic vocabulary and the characteristic vocabulary evaluation value established in advance.

The characteristic vocabulary evaluation value is used for representing the heat value corresponding to the vocabulary. The feature vocabulary library includes a plurality of feature vocabularies, and a feature evaluation value corresponding to each feature vocabulary. The feature vocabulary evaluation value corresponding to each feature vocabulary can be determined according to the corresponding relationship, and the matching degree between the text content to be transmitted and the target user can be determined based on the feature vocabulary evaluation value.

In this embodiment, the correspondence relationship between each feature word and the feature word evaluation value in the feature word library is established, and may be: for each effective task, extracting a feature vocabulary corresponding to the current effective task from a second text corresponding to the current effective task according to a preset rule template, and forming a feature vocabulary library according to the feature vocabulary of each effective task; according to each feature vocabulary, obtaining a feature vocabulary evaluation value of the current feature vocabulary based on the effective click times and the total effective click times corresponding to the current feature vocabulary; a correspondence relationship between each of the feature words and the corresponding feature word evaluation value is established to determine a feature evaluation value corresponding to the target feature word based on the correspondence relationship.

The valid task may be a task clicked by the user. The rule template is preset and can be extracted according to the text content of each short message in the completed task. In this embodiment, the extracted rule templates may include the following three types:

a. class of full subtraction: the preference information rule template with full subtraction, such as: "full minus";

b. and (4) folding and buckling: the discount information rule template with discount strength includes: "fold";

c. quota class: the preferential information rule module with preferential amount: such as: "voucher", "characterelement.

According to the regular expression grammar, the regular expression corresponding to the preference information rule template is defined as follows:

a. "full minus": "full \ d + minus \ d +", "full \ d + element minus \ d +", etc

b. "pleating": "\ d + discount", etc

c. "star", "starelement": "\ d + coupon", "\ d + yuan", etc.

Each of the preference words in the above expression may be taken as a feature word.

The second textual content may be textual content corresponding to a valid task. The feature words refer to words including the above-described preference words. The feature vocabulary library may be constructed according to the feature vocabulary of each valid task, i.e., the feature vocabulary library includes the feature vocabulary corresponding to each valid task.

According to the sent tasks and the effective tasks within the preset time length in the second embodiment, the effective click times of the tasks to which the feature words belong and the total effective click times of all the sent tasks can be determined. According to the effective click times and the total effective click times, the characteristic vocabulary evaluation value of the characteristic vocabulary can be determined. After the characteristic evaluation value corresponding to the characteristic vocabulary is determined, establishing a corresponding relation between the characteristic evaluation value and the corresponding characteristic vocabulary, so that when the task attribute information comprises the text content to be sent, whether the text content to be sent comprises the characteristic vocabulary can be determined, and the matching degree of the task to be sent of the text content to be sent is updated according to the characteristic evaluation value corresponding to the characteristic vocabulary.

S440, determining the matching degree between the current task to be sent and the target user according to the characteristic evaluation value.

After determining the feature vocabulary included in the text content to be sent and the corresponding feature vocabulary evaluation value, the matching degree between the current task to be sent and the target user can be determined according to the feature vocabulary evaluation value.

It should be noted that, for other tasks to be sent, S410 to S440 may be repeatedly executed to determine the matching degree between each task to be sent and the target user.

S450, determining a target task corresponding to the target user from the tasks to be sent according to the matching degree between the tasks to be sent and the target user.

And S460, sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

According to the technical scheme of the embodiment of the invention, the corresponding relation between the characteristic vocabulary and the corresponding characteristic vocabulary evaluation value is predetermined, the characteristic vocabulary contained in the text content to be sent and the corresponding characteristic vocabulary evaluation value can be determined according to the corresponding relation, the matching degree between the task to be sent and the target user is further determined based on the characteristic vocabulary evaluation value, and the technical effects of the matching degree between the target task and the user and the task conversion rate are improved when the target task is determined based on the matching degree.

As an alternative embodiment of the foregoing embodiment, fig. 5 is a flowchart illustrating a method for determining a target task according to a third embodiment of the present invention. As shown in fig. 5, the method includes:

and S510, starting.

S520, determining a rule template according to the text content corresponding to the sent task.

Wherein, the rule template may be a preference information template.

Specifically, each sent task has corresponding text content, and a preference template, optionally, full, discount, coupon, member, etc., may be determined for the text content.

And S530, extracting corresponding characteristic vocabularies based on the rule template.

Specifically, based on the determined benefit information template, a regular expression corresponding to the benefit information template may be determined, and optionally, "full minus": "full \ d + minus \ d +", "full \ d + element minus \ d +", "folding": "\ d + discount", "starcoupon", "starelement": the "\ d + coupon", "\ d + primitive" can use each word in the above expression as a feature word. For example, "full minus" may be used as a feature word.

S540, determining the characteristic evaluation value corresponding to the characteristic vocabulary, and establishing the corresponding relation between the characteristic vocabulary and the characteristic vocabulary evaluation value.

After the feature vocabulary is determined, the feature vocabulary evaluation value of each feature vocabulary can be determined according to the total effective click times corresponding to the sent task and the click times corresponding to the sent task to which each feature vocabulary belongs, and optionally, the ratio of the click times A corresponding to the sent task to which the feature vocabulary M belongs to and the total effective click times B is the feature vocabulary evaluation value corresponding to the feature vocabulary M.

After the characteristic words and the characteristic word evaluation values are determined, the corresponding relation between each characteristic word and each characteristic word evaluation value can be established, so that when the target task is determined, the characteristic word evaluation values are called based on the corresponding relation, the matching degree between the task to be sent and the target user is determined based on the characteristic word evaluation values, and the target task is determined according to the matching degree.

And S550, determining the characteristic vocabulary included in the text content to be sent of the current task to be sent, and determining the characteristic vocabulary evaluation value of the characteristic vocabulary according to the corresponding relation.

Specifically, the feature vocabulary included in the text content to be sent is determined, and the feature vocabulary evaluation value corresponding to the current feature vocabulary is retrieved according to the pre-established corresponding relationship.

And S560, determining the matching degree between the current task to be sent and the target user according to the characteristic vocabulary evaluation value of each characteristic vocabulary.

For example, if the text content to be sent includes five feature words A, B, C, D, E, the feature word evaluation values t (a), t (b), t (c), t (d), and t (e) of the five feature words may be determined based on the corresponding relationships, and the matching degree between the current task to be sent and the target user may be determined according to t (a), t (b), t (c), t (d), and t (e).

It should be noted that S510 to S560 may be repeatedly executed to determine the matching degree between each task to be sent and the target user.

And S570, determining the target task according to the matching degree, and sending the target task to the target terminal.

For example, the task corresponding to the highest matching degree may be used as the target task, and the target task may be sent to the target terminal corresponding to the target user.

Example four

Fig. 6 is a flowchart illustrating a method for determining a target task according to a fourth embodiment of the present invention. On the basis of the foregoing embodiment, the task attribute information further includes a task creator identifier corresponding to the current task to be sent, and a specific implementation manner of determining the matching degree between the current task to be sent and the target user according to the task attribute information may refer to detailed description of the technology of this embodiment. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein.

As shown in fig. 6, the method includes:

s610, for each task to be sent, determining task attribute information of the current task to be sent.

The task attribute information may be a task creator identifier corresponding to a current task to be sent. In order to distinguish different task creators, the task creator can be marked, and the mark can be used as a task creator identifier.

S620, according to a mapping relation between the pre-established task creator identification and the creator task conversion value, determining the creator task conversion value corresponding to the task creator identification, and determining the matching degree between the current task to be sent and the target user based on the creator task conversion value.

After the task creator completes the task creation, the created task can be sent to the corresponding user. The creator task conversion value can be understood as whether the user clicks after the task is sent to the user, the conversion value of the task is determined according to the click rate of the user, and the creator task conversion value is determined according to the conversion value of the task. The mapping relationship includes a correspondence between the task creator identification and the creator task conversion value.

Specifically, a creator identifier corresponding to the task to be sent may be determined, a corresponding creator task conversion value may be called from the mapping relationship according to the creator identifier, and a matching degree between the current task to be sent and the target user is determined according to the creator task conversion value.

Correspondingly, the matching degree between other tasks to be sent and the target user can also be determined by adopting the mode.

On the basis of the technical scheme, a mapping relation between the task creator identifier and the creator task conversion value can be established, and optionally, for each creator identifier, the number of creating tasks and the number of creating tasks corresponding to the current creator identifier are determined from sent tasks within a preset time length; aiming at each created task, determining the task click rate of the current created task according to the task click quantity corresponding to the current created task and the created task sending times of the current created task; determining a creator task conversion value of the current creator identification according to the task click rate and the number of the created tasks of each created task; and establishing a mapping relation between the creator identification and the creator task conversion value, so as to obtain the creator task conversion value corresponding to the creator identification from the mapping relation according to the creator identification to which the current task to be sent belongs.

The created task number is the task number established in the preset time length. Optionally, the number of tasks created by each task creator is determined according to the tasks sent within the preset time length. The number of times a task click may be triggered after the task is sent to the user. The task click rate may be determined based on the total number of times a certain task is sent and the number of times the task is clicked.

Specifically, for each creator identifier, the number of tasks and sent tasks corresponding to the preset duration and the current creator identifier may be obtained. And determining the sending times and the clicked times of the current sent task aiming at each sent task, and determining the click rate of the task according to the clicked times and the sending times. Based on the click through rate and the number of tasks for all sent tasks, the creator's task conversion value may be determined. After the creator task conversion value corresponding to each creator identifier is determined, a mapping relationship between the creator identifier and the creator task conversion value may be established, so that when the task attribute information of the task to be sent includes the creator identifier, the creator task conversion value corresponding to the creator identifier may be determined based on the mapping relationship, and then the matching degree between the target task and the target user may be determined based on the creator task conversion value.

S630, according to the matching degree between each task to be sent and the target user, determining the target task corresponding to the target user from each task to be sent.

And S640, transmitting the text content to be transmitted corresponding to the target task to the terminal equipment of the target user.

As an optional embodiment of the foregoing embodiment, a creator task conversion value corresponding to each task creator may be determined first, and a correspondence between the creator task conversion value and a creator identifier may be established. When the task attribute information includes the creator identifier, the matching degree between the task to be sent and the target user can be determined based on the corresponding relation.

Specifically, for each task creator, the number of tasks created and sent by the task creator within a preset time period, the task click rate of the sent task, and the task sending times of each task may be determined, and the task click rate of each task may be determined according to the task click rate of each task and the task sending times of the task. And determining a creator task conversion value corresponding to the creator identification according to the task click rate of each task and the total number of the created tasks corresponding to the creator identification.

Illustratively, the number of tasks created by the creator identified as a in one year is 5, and the number of times of sending each task is a₁、A₂、A₃、A₄、A₅The number of times B each task was clicked on can be determined₁、B₂、B₃、B₄、B₅. According to the number of times that each task is clicked and the corresponding number of times of sending, the task click rate of each task can be determined. And determining a creator task conversion value S corresponding to the creator identifier A according to the ratio between the task click rate of each task and the total task quantity, and optionally, adopting a formula S (each creation task click rate corresponding to the creator identifier)/the number of created tasks.

According to the technical scheme of the embodiment of the invention, the creator identification to which the task to be sent belongs can be determined by processing the attribute information of the task to be sent, the creator task conversion value corresponding to the creator identification can be determined, the matching degree between the task to be sent and the target user is determined according to the creator task conversion value, the target task matched with the target user is determined based on the matching degree, the matching degree between the target task and the target user is improved, and the technical effect of user experience is improved.

EXAMPLE five

Fig. 7 is a flowchart illustrating a method for determining a target task according to a fifth embodiment of the present invention. On the basis of the foregoing embodiment, the task attribute information may further include: for the task item class corresponding to the current task to be sent, a specific implementation manner for determining the matching degree between the current task to be sent and the target user according to the task attribute information may refer to the technical scheme of this embodiment. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein.

As shown in fig. 7, the method includes:

and S710, determining task attribute information of the current task to be sent for each task to be sent.

When the task creator creates a task, the item type corresponding to the task may be set in advance, and the item type corresponding to the task may be referred to as a task item type.

S720, according to the task item class corresponding to the current task to be sent, determining the matching degree between the current task to be sent and a target user.

The task item type refers to an item type which is set when the current task to be sent is created and corresponds to the current task to be sent.

In this embodiment, according to the task item class, determining the matching degree between the current task to be sent and the target user may be: acquiring a target article type associated with the target user, and determining a type association matching value according to the target article type and the task article type; determining a class association coefficient value according to the number of the task categories of the task item classes and the number of the target categories of the target item classes in the task item classes; and determining the matching degree between the current task to be sent and the target user according to the class association matching value and the class association coefficient value.

When a task is created, the three classes involved in the task can be determined, and the involved three classes can be used as task item classes. Meanwhile, the target article type corresponding to the target user, namely the article type preferred by the target user, can be obtained. The associated matching value refers to a matching degree between the task item class and the target item class. The corresponding task category number can be determined according to the task item type, and the corresponding target category number can be determined according to the target item type. And determining the number of target categories included in the task category number, and determining the category association coefficient value according to the included number relation. According to the class association coefficient value and the class association matching value, the matching degree between the current task to be sent and the target user can be determined.

In this embodiment, the determining a class association matching value according to the target item class and the task item class includes: determining a task three-level category included in the task item category and a target three-level category corresponding to the target item category; determining a target tertiary category included in the task tertiary category to obtain a matched tertiary category; and respectively determining a matching value corresponding to each matching tertiary category, and taking the maximum matching value as the associated matching value of the category.

Specifically, the item-class association matching value is determined, the task item class and the third-level class of the target item class can be matched, the highest preference value of all the hit items is taken, and the determined value is used as the item-class association matching value.

It should be noted that the smaller the number of task item classes, the higher the matching correlation coefficient value. The item class association coefficient value may be determined according to the number of target item classes included in the task item class, and optionally, the item class association coefficient value is 1/log by using a formula₂(1+ number of three-level categories corresponding to task item categories/number of target item categories included in task item categories). In this embodiment, the matching degree between the current task to be sent and the target user may be determined according to a product of the class association matching value and the class association coefficient value.

And S730, determining a target task corresponding to the target user from the tasks to be sent according to the matching degree between the tasks to be sent and the target user.

And S740, sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

According to the technical scheme of the embodiment of the invention, the matching degree between the task to be sent and the target user can be determined by determining the relation between the task item class and the target item class, so that the target task corresponding to the target user is determined based on the matching degree, the triggering probability of the target task is improved, and the technical effect of marketing is achieved.

EXAMPLE six

Fig. 8 is a flowchart illustrating a method for determining a target task according to a sixth embodiment of the present invention. On the basis of the foregoing embodiment, the task attribute information may include a plurality of text contents to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent, and task item categories corresponding to the current task to be sent. When the number of the task attribute information is multiple, a specific implementation manner of determining the matching degree between the current task to be sent and the target user according to the task attribute information may refer to the technical solution of this embodiment. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein.

As shown in fig. 8, the method includes:

and S810, determining task attribute information of the current task to be sent for each task to be sent.

The task attribute information may include a plurality of text contents to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent, and task item categories corresponding to the current task to be sent.

S820, determining the matching degree between the current task to be sent and the target user according to the matching degree corresponding to at least one task attribute information.

When the number of the task attribute information includes a plurality of pieces, each piece of task attribute information may be processed, and the matching degree corresponding to each piece of task attribute information may be obtained. And obtaining the matching degree between the current task to be sent and the target user according to the matching degree corresponding to each task attribute information.

In this embodiment, the determining the matching degree between the current task to be sent and the target user according to the matching degree corresponding to at least one task attribute information includes: and determining the matching degree between the current task to be sent and the target user according to the weight value and the matching degree corresponding to each task attribute information.

The weight value corresponding to each task attribute information can be preset, optionally, the weight value corresponding to the text content to be sent is set to be A, the weight value corresponding to the creator identifier corresponding to the current task to be sent is set to be B, and the weight value corresponding to the task article class corresponding to the current task to be sent is set to be C. According to the matching degree corresponding to each task attribute information and the weight value corresponding to each task attribute information, the matching degree between the current task to be sent and the target user can be determined.

Illustratively, the weight value corresponding to the text content to be sent is a, the corresponding matching degree is p (a), the weight value corresponding to the creator identifier is B, the corresponding matching value is t (B), the weight value corresponding to the task item class is C, and the corresponding matching value is s (C), and the matching degree corresponding to the current task to be sent is determined based on the above values: a + P (A) + B + T (B) + C + S (C).

And S830, determining a target task corresponding to the target user from the tasks to be sent according to the matching degree between the tasks to be sent and the target user.

Specifically, the matching degree of each task to be sent can be determined by repeatedly executing the steps, and the target task corresponding to the target user can be determined from each task to be sent according to the matching degree between each task to be sent and the target user.

In this embodiment, determining the target task corresponding to the target user according to the matching degree may be: and determining the task to be sent corresponding to the highest matching degree according to the matching degree between each task to be sent and the target user, and taking the task to be sent as the target task corresponding to the target user.

Specifically, according to the matching degree of each task to be sent, the task to be sent with the highest matching degree can be used as the target task corresponding to the target user.

The method for determining the target task has the advantages that the task with the highest degree of engagement with the target user can be screened from all tasks to be sent, and when the task is sent to the corresponding target user, the probability that the target user triggers the target task can be improved, so that the task conversion rate is improved, and the technical effect of achieving the marketing purpose is achieved.

And S840, sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

According to the technical scheme of the embodiment of the invention, the matching degree between the task to be sent and the target user can be determined by processing the task attribute information corresponding to each task to be sent, so that the task to be sent with the highest matching degree is sent to the target user, the conformity between the determined target task and the user is improved, the task triggering probability is improved, and the technical effect of the task conversion rate is improved.

EXAMPLE seven

Fig. 9 is a schematic structural diagram of an apparatus for determining a target task according to a seventh embodiment of the present invention, where the apparatus includes: a matching degree determining module 910, a target task determining module 920 and a target task sending module 930.

The matching degree determining module 910 is configured to determine, for each task to be sent, task attribute information of a current task to be sent, and determine, according to the task attribute information, a matching degree between the current task to be sent and a target user; the task attribute information comprises at least one of text content to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent and a task article class corresponding to the current task to be sent; a target task determining module 920, configured to determine, according to a matching degree between each task to be sent and a target user, a target task corresponding to the target user from each task to be sent; a target task sending module 930, configured to send the text content to be sent corresponding to the target task to the terminal device of the target user. On the basis of the above, the apparatus further includes:

the sample set generation module is used for acquiring the sent tasks and the total sending times within the preset time length and clicking the effective tasks and the total effective clicking times of the sent tasks; generating a sample set based on the sent tasks, the total sending times, the effective tasks and the total effective click times; the system comprises a related vocabulary set generation module, a word segmentation tool generation module and a word group model generation module, wherein the related vocabulary set generation module is used for processing first text content of a current sent task and determining related vocabulary of the current sent task based on the word segmentation tool, a preset stop vocabulary and a preset word group model; generating a related vocabulary set according to the related vocabulary of each sent task; the association value determining module is used for determining the sending times and the effective click times of at least one sent task to which the current association vocabulary belongs according to each association vocabulary in the association vocabulary set, determining the heat value of the current association vocabulary according to the sending times and the total sending times of the vocabulary, and determining the effective trigger value of the current association vocabulary according to the effective click times and the total effective click times; determining a total trigger value of the current associated vocabulary according to the total effective click times and the total sending times; and the storage module is used for correspondingly storing each associated vocabulary, and the heat value, the effective trigger value and the total trigger value corresponding to the associated vocabulary to a preset position so as to determine the matching degree between the task to be sent and the target user according to the stored heat value, the stored effective trigger value and the stored total trigger value.

On the basis of the above technical solutions, the associated vocabulary set generating module further includes:

the vocabulary to be used determining unit is used for dividing the first text content into at least one vocabulary to be processed based on the word segmentation tool; removing the vocabulary which is the same as the preset disabled vocabulary from the at least one vocabulary to be processed to obtain at least one vocabulary to be used; the to-be-used phrase determining unit is used for combining the at least one to-be-used vocabulary into at least one to-be-used phrase based on the preset phrase model and the position information of the at least one to-be-used vocabulary in the first text content; and the associated vocabulary determining unit is used for determining the associated vocabulary of the current task to be sent based on the at least one vocabulary to be used and the at least one phrase to be used.

On the basis of the technical schemes, the to-be-used phrase determining unit is used for determining a sub-unit of the to-be-processed phrase and is used for combining two adjacent to-be-used vocabularies of the position information into the to-be-processed phrase based on a preset phrase model; and the to-be-used phrase determining subunit is used for taking the to-be-processed phrase as the to-be-used phrase if the to-be-processed phrase is consistent with part of the content in the first text content.

On the basis of the above technical solutions, the matching degree determining module is further configured to: determining at least one target associated vocabulary corresponding to the text content to be sent; for each target associated vocabulary, calling a heat value and an effective trigger value corresponding to the current target associated vocabulary from the preset position; and determining the matching degree between the current task to be sent and the target user according to the heat value, the effective trigger value and the total trigger value of each target associated vocabulary.

On the basis of the above technical solutions, the matching degree determining module is further configured to: determining a first intermediate processing value corresponding to the current task to be sent according to the effective trigger value and the total trigger value of each target associated vocabulary; determining a second intermediate processing value of the current task to be sent according to the heat value of each target associated vocabulary; and determining the matching degree between the current task to be sent and the target user based on the first intermediate processing value and the second intermediate processing value.

On the basis of the above technical solutions, the matching degree determining module is further configured to: determining target feature words included in the text to be sent according to each feature word in a feature word library;

determining the characteristic evaluation value of each target characteristic vocabulary according to the corresponding relation between the characteristic vocabulary and the characteristic vocabulary evaluation value established in advance;

and determining the matching degree between the current task to be sent and the target user according to the characteristic evaluation value.

On the basis of the above technical solutions, the apparatus further includes: a correspondence establishing module, configured to: establishing a corresponding relation between the characteristic words and the characteristic word evaluation values;

the establishing of the correspondence between the feature vocabulary and the feature vocabulary evaluation value includes:

for each effective task, extracting a feature vocabulary corresponding to the current effective task from a second text corresponding to the current effective task according to a preset rule template, and forming a feature vocabulary library according to the feature vocabulary of each effective task; according to each feature vocabulary, obtaining a feature vocabulary evaluation value of the current feature vocabulary based on the effective click times and the total effective click times corresponding to the current feature vocabulary; a correspondence relationship between each of the feature words and the corresponding feature word evaluation value is established to determine a feature evaluation value corresponding to the target feature word based on the correspondence relationship.

On the basis of the above technical solutions, the matching degree determining module is further configured to: determining a creator task conversion value corresponding to the task creator identification according to a mapping relation between a pre-established task creator identification and a creator task conversion value, and determining the matching degree between the current task to be sent and the target user based on the creator task conversion value.

On the basis of the above technical solutions, the apparatus further includes: a mapping relationship establishing module for: establishing a mapping relation between a task creator identifier and a creator task conversion value;

the establishing of the mapping relationship between the task creator identification and the creator task conversion value comprises the following steps:

aiming at each creator identification, determining the number of creating tasks and creating tasks corresponding to the current creator identification from the sent tasks within a preset time length; aiming at each created task, determining the task click rate of the current created task according to the task click quantity corresponding to the current created task and the created task sending times of the current created task; determining a creator task conversion value of the current creator identification according to the task click rate of each creation task and the number of the creation tasks;

and establishing a mapping relation between the creator identification and the creator task conversion value, so as to obtain the creator task conversion value corresponding to the creator identification from the mapping relation according to the creator identification to which the current task to be sent belongs.

On the basis of the above technical solutions, the task attribute information includes a task item class corresponding to the current task to be sent, and the matching degree determining module is further configured to: acquiring a target article type associated with the target user, and determining a type association matching value according to the target article type and the task article type;

determining a class association coefficient value according to the number of the task categories of the task item classes and the number of the target categories of the target item classes in the task item classes;

and determining the matching degree between the current task to be sent and the target user according to the class association matching value and the class association coefficient value.

On the basis of the above technical solutions, the matching degree determining module is further configured to: determining a task three-level category included in the task item category and a target three-level category corresponding to the target item category; determining a target tertiary category included in the task tertiary category to obtain a matched tertiary category; and respectively determining a matching value corresponding to each matching tertiary category, and taking the maximum matching value as the associated matching value of the category.

On the basis of the above technical solutions, the matching degree determining module is further configured to: and determining the matching degree between the current task to be sent and the target user according to the matching degree corresponding to at least one task attribute information.

On the basis of the above technical solutions, the matching degree determining module is further configured to: and determining the matching degree between the current task to be sent and the target user according to the weight value and the matching degree corresponding to each task attribute information.

On the basis of the above technical solutions, the target task determining module is further configured to determine, according to the matching degree between each task to be sent and the target user, the corresponding task to be sent when the matching degree is highest, and take the task to be sent as the target task corresponding to the target user.

According to the technical scheme of the embodiment of the invention, the matching degree between each task to be sent and the target user can be determined by processing the task attribute information of each task to be sent, so that the target task is determined from each task to be sent based on the matching degree, the matching degree between the determined target task and the target user is improved, and then the target task can be sent to the terminal corresponding to the target user after the target task is determined.

The device for determining the target task, provided by the embodiment of the invention, can execute the method for determining the target task, provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

It should be noted that, the units and modules included in the apparatus are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the embodiment of the invention.

Example eight

Fig. 10 is a schematic structural diagram of an apparatus according to an eighth embodiment of the present invention. FIG. 10 illustrates a block diagram of an exemplary device 100 suitable for use in implementing embodiments of the present invention. The device 100 shown in fig. 10 is only an example and should not bring any limitation to the function and the scope of use of the embodiments of the present invention.

As shown in FIG. 10, device 100 is embodied in a general purpose computing device. The components of the device 100 may include, but are not limited to: one or more processors or processing units 1001, a system memory 1002, and a bus 1003 that couples the various system components (including the system memory 1002 and the processing unit 1001).

Bus 1003 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Device 100 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by device 100 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 1002 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)1004 and/or cache memory 1005. The device 100 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 1006 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 10, commonly referred to as a "hard disk drive"). Although not shown in FIG. 10, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 1003 by one or more data media interfaces. Memory 1002 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.

A program/utility 1008 having a set (at least one) of program modules 1007 may be stored, for example, in memory 1002, such program modules 1007 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may include an implementation of a network environment. Program modules 1007 generally perform functions and/or methods in the described embodiments of the invention.

Device 100 may also communicate with one or more external devices 1009 (e.g., keyboard, pointing device, display 1010, etc.), with one or more devices that enable a user to interact with device 100, and/or with any devices (e.g., network card, modem, etc.) that enable device 100 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 1011. Also, the device 100 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 1012. As shown, the network adapter 1012 communicates with the other modules of the device 100 via the bus 1003. It should be appreciated that although not shown in FIG. 10, other hardware and/or software modules may be used in conjunction with device 100, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

The processing unit 1001 executes various functional applications and data processing, such as a method of determining a target task provided by an embodiment of the present invention, by executing a program stored in the system memory 1002.

Example nine

An embodiment of the present invention also provides a storage medium containing computer-executable instructions for performing a method of determining a target task when executed by a computer processor.

The method comprises the following steps:

for each task to be sent, determining task attribute information of the current task to be sent, and determining the matching degree between the current task to be sent and a target user according to the task attribute information; the task attribute information comprises at least one of text content to be sent corresponding to the current task to be sent, a task creator identifier corresponding to the current task to be sent and a task article class corresponding to the current task to be sent;

determining a target task corresponding to a target user from each task to be sent according to the matching degree between each task to be sent and the target user;

and sending the text content to be sent corresponding to the target task to the terminal equipment of the target user.

Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.