阅读说明：本技术 基于兴趣点的状态信息发布方法、系统、设备及存储介质 (Method, system, equipment and storage medium for publishing state information based on interest points ) 是由 刘晓妍 江小林 雷志丹 罗超 许智蔚 程国强 于 2021-09-17 设计创作，主要内容包括：本发明提供了基于兴趣点的状态信息发布方法、系统、设备及存储介质,该方法包括：获得至少一兴趣点的电话号码；通过AI语音机器人采用预设对话模板与兴趣点的电话号码进行通话,采集兴趣点的预设结构化信息,预设结构化信息至少包括地址和营业时间；将兴趣点的预设结构化信息发布于网络交互平台。本发明能够自动收集兴趣点的状态信息,避免了人力投入,降低了运营成本,保证了网络交互平台所公布信息的准确性。(The invention provides a state information issuing method, a system, equipment and a storage medium based on interest points, wherein the method comprises the following steps: obtaining a telephone number of at least one interest point; the AI voice robot adopts a preset dialogue template to communicate with the telephone number of the interest point, and collects the preset structural information of the interest point, wherein the preset structural information at least comprises an address and business hours; and issuing the preset structured information of the interest points to a network interaction platform. The invention can automatically collect the state information of the interest points, avoids the manpower input, reduces the operation cost and ensures the accuracy of the information published by the network interaction platform.)

1. A state information publishing method based on interest points is characterized by comprising the following steps:

s110, obtaining a telephone number of at least one interest point;

s120, communicating with the telephone number of the interest point by using a preset conversation template through the AI voice robot, and collecting preset structural information of the interest point, wherein the preset structural information at least comprises an address and business hours; and

s140, the preset structured information of the interest points is issued to a network interaction platform.

2. The method for releasing the state information based on the point of interest according to claim 1, wherein the step S110 comprises:

and capturing the telephone number of at least one interest point from the public opinion data through the first web crawler.

3. The method for releasing the state information based on the point of interest according to claim 2, wherein the step S120 comprises:

s121, communicating with the telephone number of the interest point through the AI voice robot;

s122, sequentially asking questions by an AI voice robot by adopting a preset dialogue template, wherein each preset field in the preset dialogue template comprises a corresponding question, the preset field at least comprises an address and business hours, and a reply audio is recorded;

s123, performing voice recognition on the reply audio to obtain a reply text, and establishing a mapping relation between the reply text and a preset field;

and S124, filling the keywords in the reply text into the corresponding preset fields through natural language processing.

4. The method for publishing point of interest based status information according to claim 1, wherein after the step S140, the method further comprises the steps of:

s151, capturing complaints about the suspended business class of at least one interest point from public opinion data through a second web crawler, and taking the interest point as a target interest point;

and S160, communicating with the telephone number of the target interest point by the AI voice robot by adopting a preset conversation template, and updating the preset structured information.

5. The method for publishing point of interest based status information according to claim 1, wherein after the step S120, the method further comprises the steps of:

s130, establishing an adjacent interest point set of the interest points located in the same building based on the addresses of the interest points;

after the step S140, the method further includes the following steps:

s152, capturing complaints about the pause business class of at least one interest point from public opinion data through a second web crawler, and taking other interest points which are positioned in the same adjacent interest point set with the interest point as target interest points;

and S160, communicating with the telephone number of the target interest point by using a preset conversation template through the AI voice robot, and updating when the preset structural information changes.

6. The method for issuing point of interest-based status information according to claim 5, further comprising the following steps after said step S160:

s170, when the nearby interest point set has interest points exceeding a preset proportion and the business is suspended, supplementing a business suspension prompt for the display page of all the interest points in the nearby interest point set on the network interaction platform.

7. The method for issuing point of interest-based status information according to claim 4 or 5, further comprising the following steps after said step S170:

and S180, based on a preset period, calling the telephone number of the interest point which is temporarily stopped by the AI voice robot by adopting a preset dialogue template, and updating preset structural information of the interest point, wherein the preset structural information at least comprises an address and business time, and the value range of the preset period is 3 days to 3 months.

8. An interest-based status information distribution system for implementing the interest-based status information distribution method according to claim 1, comprising:

the telephone number acquisition module is used for acquiring the telephone number of at least one interest point;

the structural information module is used for calling with the telephone number of the interest point by adopting a preset dialogue template through the AI voice robot and acquiring preset structural information of the interest point, wherein the preset structural information at least comprises an address and business hours; and

and the platform information issuing module is used for issuing the preset structured information of the interest points to a network interaction platform.

9. A point-of-interest-based status information distribution device, comprising:

a processor;

a memory having stored therein executable instructions of the processor;

wherein the processor is configured to perform the steps of the point of interest based state information publishing method of any one of claims 1 to 7 via execution of the executable instructions.

10. A computer-readable storage medium storing a program, wherein the program, when executed by a processor, implements the steps of the point-of-interest-based status information distribution method according to any one of claims 1 to 7.

Technical Field

The present invention relates to the field of information updating, and in particular, to a method, system, device, and storage medium for publishing state information based on points of interest.

Background

POI is an abbreviation for "Point of Interest" and Chinese can be translated into "points of Interest". In the geographic information system, one POI may be one house, one shop, one mailbox, one bus station, and the like. The traditional geographic information acquisition method requires a mapping staff to acquire the longitude and latitude of an information point by using a precise mapping instrument and then mark the information point. Just as the collection of POIs is a very time-consuming and laborious task, for a geographic information system, the number of POIs represents the value of the whole system to some extent.

Each POI comprises four-aspect information, name, category, coordinate and classification, comprehensive POI information is necessary information for enriching a navigation map, timely POI information points can remind a user of branches of road conditions and detailed information of surrounding buildings, all places required by the user can be conveniently searched in navigation, and the most convenient and unobstructed road is selected for path planning, so that the good use degree of the navigation is directly influenced by the POI conditions of the navigation map.

The intelligent customer service is widely applied in various industries, and various enterprises have own outbound systems or intelligent conversation robots. Some existing dialog systems mainly acquire required information through multiple rounds of dialog interaction, and in the multiple rounds of dialog interaction, dialog flow design, dialog management and the like need to be implemented. The current mainstream method is a finite state machine-based method, that is, a dialog is performed according to a designed dialog flow, information of a user is acquired, and the dialog is performed through state conversion. However, in actual use, there are the following problems:

1. taking POI information of restaurants as an example, the number of restaurant POIs recorded and recorded by the platform a is huge, the recording amount of a continental restaurant is as high as about 400w, and the information of the restaurant POIs of 389.3w is difficult to maintain timely, accurately and effectively. According to statistics, 10% of complaints of customers in the daily operation and maintenance process are caused by inaccurate business hours and open states, mislead the users and cause dissatisfaction of the users.

2. The crawler (big data update) strongly depends on the accuracy of the external information and the accuracy of the matching algorithm, the accuracy of the external information is difficult to guarantee, the time and labor consumption of the update is high, and the cost is high.

3. The merchant maintenance and the business maintenance strongly depend on the platform A and the merchant to establish a cooperative relationship, but most restaurants have no cooperative relationship and have a small maintainability range.

Therefore, the POI information is recorded and maintained difficultly by manpower, updating is not timely, and the maintenance cost is high.

In individual cases, the interaction platform a publishes much POI information, but encounters, for example: when the living square is integrally decorated, how many shops can not be operated, and after a plurality of users guide a target interest point (restaurant) according to the route of the interaction platform A, the state that the shop can not be operated can be found, and the state is not consistent with the state displayed in the interaction platform A, so that the trust evaluation of the users on the interaction platform A can be seriously reduced.

Therefore, the invention provides a method, a system, equipment and a storage medium for publishing state information based on interest points.

Disclosure of Invention

Aiming at the problems in the prior art, the invention aims to provide a state information publishing method, a system, equipment and a storage medium based on points of interest, which overcome the difficulties in the prior art, can automatically collect the state information of the points of interest, avoid the manpower input, reduce the operation cost and ensure the accuracy of the information published by a network interaction platform.

The embodiment of the invention provides a state information issuing method based on an interest point, which comprises the following steps:

s110, obtaining a telephone number of at least one interest point;

s120, communicating with the telephone number of the interest point by using a preset conversation template through the AI voice robot, and collecting preset structural information of the interest point, wherein the preset structural information at least comprises an address and business hours; and

s140, the preset structured information of the interest points is issued to a network interaction platform.

Preferably, the step S110 includes:

and capturing the telephone number of at least one interest point from the public opinion data through the first web crawler.

Preferably, the step S120 includes:

s121, communicating with the telephone number of the interest point through the AI voice robot;

s122, sequentially asking questions by an AI voice robot by adopting a preset dialogue template, wherein each preset field in the preset dialogue template comprises a corresponding question, the preset field at least comprises an address and business hours, and a reply audio is recorded;

s123, performing voice recognition on the reply audio to obtain a reply text, and establishing a mapping relation between the reply text and a preset field;

and S124, filling the keywords in the reply text into the corresponding preset fields through natural language processing.

Preferably, after the step S140, the method further comprises the following steps:

s151, capturing complaints about the suspended business class of at least one interest point from public opinion data through a second web crawler, and taking the interest point as a target interest point;

and S160, communicating with the telephone number of the target interest point by the AI voice robot by adopting a preset conversation template, and updating the preset structured information.

Preferably, after the step S120, the method further includes the following steps:

s130, establishing an adjacent interest point set of the interest points located in the same building based on the addresses of the interest points;

after the step S140, the method further includes the following steps:

s152, capturing complaints about the pause business class of at least one interest point from public opinion data through a second web crawler, and taking other interest points which are positioned in the same adjacent interest point set with the interest point as target interest points;

and S160, communicating with the telephone number of the target interest point by using a preset conversation template through the AI voice robot, and updating when the preset structural information changes.

Preferably, after the step S160, the method further includes the following steps:

s170, when the nearby interest point set has interest points exceeding a preset proportion and the business is suspended, supplementing a business suspension prompt for the display page of all the interest points in the nearby interest point set on the network interaction platform.

Preferably, after the step S170, the method further includes the following steps:

and S180, based on a preset period, calling the telephone number of the interest point which is temporarily stopped by the AI voice robot by adopting a preset dialogue template, and updating preset structural information of the interest point, wherein the preset structural information at least comprises an address and business time, and the value range of the preset period is 3 days to 3 months.

An embodiment of the present invention further provides a state information publishing system based on the point of interest, which is used to implement the above state information publishing method based on the point of interest, and the state information publishing system based on the point of interest includes:

the telephone number acquisition module is used for acquiring the telephone number of at least one interest point;

the structural information module is used for calling with the telephone number of the interest point by adopting a preset dialogue template through the AI voice robot and acquiring preset structural information of the interest point, wherein the preset structural information at least comprises an address and business hours; and

and the platform information issuing module is used for issuing the preset structured information of the interest points to a network interaction platform.

The embodiment of the present invention further provides a device for publishing state information based on points of interest, including:

a processor;

a memory having stored therein executable instructions of the processor;

wherein the processor is configured to perform the steps of the point of interest based state information publication method described above via execution of the executable instructions.

An embodiment of the present invention further provides a computer-readable storage medium for storing a program, where the program implements the steps of the above-mentioned point-of-interest-based status information publishing method when executed.

The invention aims to provide a method, a system, equipment and a storage medium for releasing state information based on points of interest, which can automatically collect the state information of the points of interest, avoid human input, reduce operation cost and ensure the accuracy of information released by a network interaction platform.

Drawings

Other features, objects and advantages of the present invention will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings.

Fig. 1 is a flowchart of a method for publishing point-of-interest-based status information according to the present invention.

FIG. 2 is an interface diagram of an implementation process of the method for publishing the state information based on the point of interest according to the present invention.

Fig. 3 is a schematic block diagram of a point of interest-based status information distribution system according to the present invention.

Fig. 4 is a schematic structural diagram of a point-of-interest-based status information distribution apparatus according to the present invention.

Fig. 5 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present application is provided by way of specific examples, and other advantages and effects of the present application will be readily apparent to those skilled in the art from the disclosure herein. The present application is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present application. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

Embodiments of the present application will be described in detail below with reference to the accompanying drawings so that those skilled in the art to which the present application pertains can easily carry out the present application. The present application may be embodied in many different forms and is not limited to the embodiments described herein.

Reference throughout this specification to "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," or the like, means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. Furthermore, the particular features, structures, materials, or characteristics shown may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of different embodiments or examples presented in this application can be combined and combined by those skilled in the art without contradiction.

Furthermore, the terms "first", "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the expressions of the present application, "plurality" means two or more unless specifically defined otherwise.

In order to clearly explain the present application, components that are not related to the description are omitted, and the same reference numerals are given to the same or similar components throughout the specification.

Throughout the specification, when a device is referred to as being "connected" to another device, this includes not only the case of being "directly connected" but also the case of being "indirectly connected" with another element interposed therebetween. In addition, when a device "includes" a certain component, unless otherwise stated, the device does not exclude other components, but may include other components.

When a device is said to be "on" another device, this may be directly on the other device, but may also be accompanied by other devices in between. When a device is said to be "directly on" another device, there are no other devices in between.

Although the terms first, second, etc. may be used herein to describe various elements in some instances, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, the first interface and the second interface are represented. Also, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, items, species, and/or groups thereof. The terms "or" and/or "as used herein are to be construed as inclusive or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a", "an" and "the" include plural forms as long as the words do not expressly indicate a contrary meaning. The term "comprises/comprising" when used in this specification is taken to specify the presence of stated features, regions, integers, steps, operations, elements, and/or components, but does not exclude the presence or addition of other features, regions, integers, steps, operations, elements, and/or components.

Although not defined differently, including technical and scientific terms used herein, all terms have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. Terms defined in commonly used dictionaries are to be additionally interpreted as having meanings consistent with those of related art documents and the contents of the present prompts, and must not be excessively interpreted as having ideal or very formulaic meanings unless defined.

Fig. 1 is a flowchart of a method for publishing point-of-interest-based status information according to the present invention. As shown in fig. 1, an embodiment of the present invention provides a method for publishing state information based on points of interest, including the following steps:

s110, obtaining the telephone number of at least one interest point.

And S120, the AI voice robot adopts a preset dialogue template to communicate with the telephone number of the interest point, and collects preset structural information of the interest point, wherein the preset structural information at least comprises an address and business hours. And

s140, publishing the preset structured information of the interest point to the network interaction platform, but not limited thereto.

In a preferred embodiment, step S110 includes:

the first web crawler captures the phone number of at least one interest point from the public opinion data, but not limited thereto.

In a preferred embodiment, step S120 includes:

and S121, calling with the telephone number of the interest point through the AI voice robot.

And S122, sequentially asking questions by the AI voice robot by adopting a preset dialogue template, wherein each preset field in the preset dialogue template comprises a corresponding question, the preset fields at least comprise an address and business hours, and reply audios are recorded.

And S123, performing voice recognition on the reply audio to obtain a reply text, and establishing a mapping relation between the reply text and the preset field.

S124, filling the keywords in the reply text into the corresponding preset fields through natural language processing, but not limited thereto.

In this embodiment, the existing speech recognition and the existing natural language processing technology are adopted.

Among them, Natural Language Processing (NLP) is an important direction in the fields of computer science and artificial intelligence. It studies various theories and methods that enable efficient communication between humans and computers using natural language. Natural language processing is a science integrating linguistics, computer science and mathematics. Therefore, the research in this field will relate to natural language, i.e. the language that people use everyday, so it is closely related to the research of linguistics, but has important difference. Natural language processing is not a general study of natural language but is directed to the development of computer systems, and particularly software systems therein, that can efficiently implement natural language communications. It is thus part of computer science. The natural language processing is mainly applied to the aspects of machine translation, public opinion monitoring, automatic summarization, viewpoint extraction, text classification, question answering, text semantic comparison, voice recognition, Chinese OCR and the like.

Speech recognition is a cross discipline. In the last two decades, speech recognition technology has advanced significantly, starting to move from the laboratory to the market. The fields to which speech recognition technology relates include: signal processing, pattern recognition, probability and information theory, sound and hearing mechanisms, artificial intelligence, and the like. The speech recognition tasks can be generally classified into 3 categories, i.e., isolated word recognition (isolated word recognition), keyword recognition (or keyword spotting), and continuous speech recognition, according to the recognized objects. The task of the isolated word recognition is to recognize isolated words known in advance, such as 'power on', 'power off', and the like; the task of continuous speech recognition is to recognize any continuous speech, such as a sentence or a segment of speech; keyword detection in a continuous speech stream is for continuous speech, but it does not recognize all words, but only detects where known keywords appear, such as detecting the words "computer", "world" in a passage of speech. The voice recognition method mainly comprises the following steps: in the training phase, the user speaks each word in the vocabulary in turn and stores its feature vectors as templates into a template library. In the recognition stage, the feature vector of the input voice is compared with each template in the template library in similarity in sequence, and the highest similarity is output as a recognition result.

In a preferred embodiment, after step S140, the following steps are further included:

and S151, capturing complaints about the suspended business class of at least one interest point from public opinion data through a second web crawler, and taking the interest points as target interest points.

And S160, communicating with the telephone number of the target interest point by the AI voice robot by adopting a preset conversation template, and updating the preset structured information, but not limited to the preset structured information.

In a preferred embodiment, after step S120, the following steps are further included:

s130, establishing a set of adjacent interest points for the interest points located in the same building based on the address establishment of the interest points, and forming the set of adjacent interest points through positioning clustering of the GPS technology in the prior art or similarity determination of address texts in the prior art, but not limited thereto.

After step S140, the method further includes the following steps:

s152, capturing complaints about the pause business class of at least one interest point from public opinion data through a second web crawler, and taking other interest points which are located in the same adjacent interest point set with the interest point as target interest points.

And S160, the AI voice robot adopts a preset dialogue template to communicate with the telephone number of the target interest point, and when the preset structural information changes, the AI voice robot updates the preset structural information, but not limited to the preset dialogue template.

In a preferred embodiment, after step S160, the following steps are further included:

and S170, when the nearby interest point set has interest points exceeding the preset proportion and the business is suspended, supplementing the business suspension reminding for the display pages of all the interest points in the nearby interest point set on the network interaction platform, but not limiting the operation.

In a preferred embodiment, after step S170, the following steps are further included:

and S180, based on a preset period, the AI voice robot adopts a preset dialogue template to communicate with the telephone number of the interest point which is temporarily stopped to operate, the preset structural information of the interest point is updated, the preset structural information at least comprises an address and operating time, and the value range of the preset period is 3 days to 3 months, but not limited to the range.

The invention uses a brand-new updating means and mode to update and maintain restaurant information. By means of the mode that the AI voice robot model interacts with restaurant merchants and obtains fixed-point information, the large-volume restaurant POI information can be effectively and timely maintained.

FIG. 2 is an interface diagram of an implementation process of the method for publishing the state information based on the point of interest according to the present invention. As shown in fig. 2, each of the buildings 1, 2, 3, 4 has a plurality of interest points.

First, the first web crawler captures the phone number of at least one point of interest from the network data, for example, the phone numbers of the points of interest 21, 22, 23, 24, 25, 26 in the building 2 are obtained.

Then, the AI voice robot makes a call with the telephone numbers of the points of interest 21, 22, 23, 24, 25, and 26, respectively. And sequentially asking questions by using a preset dialogue template through the AI voice robot.

In this embodiment, the preset dialog mode mainly includes the following processes, but not limited to: [ call completion ], [ call admission ], [ incoming call intention ], [ check restaurant name and business state ], [ check restaurant address ], [ check business time ], [ end of call ], [ return information ], and [ calibrate restaurant information according to the return information ]. The restaurant name, the business state, the restaurant address and the business time are four preset fields in the preset dialogue template. Each preset field in the preset dialog template includes a corresponding question, the preset field includes at least an address and business hours, and a reply audio is recorded. And performing voice recognition on the reply audio to obtain a reply text, and establishing a mapping relation between the reply text and the preset field. And filling the keywords in the reply text into the corresponding preset fields through natural language processing. For example: the AI voice robot asks: "do your business hours? "shop answer voice: the method comprises the steps of identifying the answer voice of a shop to be a text from '9 am to 9 pm', obtaining '9 am to 9 pm' text information, extracting keywords from the text information '9 am to 9 pm' through the existing natural semantic processing method, and filling the keywords into the values of corresponding preset fields.

Building 2 is taken as an example, the interest points 21, 22, 23, 24, 25, and 26 together form a near interest point set 20.

And releasing the preset structured information of the interest points 21, 22, 23, 24, 25 and 26 to the network interaction platform B.

And capturing complaints about the pause business class of at least one interest point from the network data through a second web crawler, and taking other interest points which are positioned in the same adjacent interest point set as the interest points as target interest points. For example, the existing natural semantic recognition hiccup detects that the user leaves a message in the latest comment block of the interest point 21 in the network interaction platform B is recognized to be "closed", and the user does not eat a comment expressing a suspended business class such as "at decoration". Subsequently, a plurality of other interest points in the same neighboring interest point set as the interest point 21 are randomly selected as the target interest point (one of the interest points 22, 23, 24, 25, and 26, two of the interest points 22 and 23 are selected in this embodiment).

The AI voice robot uses a preset dialogue template to communicate with the telephone numbers of two target points of interest (points of interest 22 and 23), and updates the preset structured information when the preset structured information changes, but not limited to this.

And finally, the AI voice robot adopts a preset dialogue template to respectively communicate with the telephone numbers of the target interest points (the interest points 22 and 23) and updates the preset structured information. (interest points 22 and 23 are both out of business)

When the nearby interest point set has more than 30% of the interest points in the nearby interest point set, which are in excess of the preset percentage (in this embodiment, 33.3% of the nearby interest points in the nearby interest point set are in suspension), it indicates that the building is likely to be under overhaul, most stores cannot be in suspension, and the network interaction platform B supplements the suspension operation reminder for the display pages of all the interest points in the nearby interest point set (the interest points 21, 22, 23, 24, 25, 26).

And based on a preset period (every month), performing a return visit call with the phone numbers of the interest points (the interest points 21, 22, 23, 24, 25, 26) which are temporarily out of business by using a preset dialogue template through the AI voice robot, updating preset structured information of the interest points, wherein the preset structured information at least comprises addresses and business hours, and after confirming that the interest points 21, 22, 23, 24, 25, 26 are respectively re-opened, updating the structured information corresponding to each interest point on the network interaction platform B.

In the process, the influence of the emergency on information such as business state in the structured information can be achieved in a self-learning mode without human intervention.

Fig. 3 is a schematic block diagram of a point of interest-based status information distribution system according to the present invention. As shown in fig. 3, the point-of-interest-based status information distribution system 5 of the present invention includes:

the phone number acquisition module 51 obtains a phone number of at least one point of interest.

The structured information module 52 uses a preset dialogue template to communicate with the phone number of the interest point through the AI voice robot, and collects preset structured information of the interest point, where the preset structured information at least includes an address and business hours.

The point of interest integration module 53 establishes a set of neighboring points of interest for points of interest that will be located within the same building based on the address of the points of interest.

The platform information publishing module 54 publishes the preset structured information of the interest point to the network interaction platform.

The pause business class module 55 captures a complaint about the pause business class of at least one point of interest from the public opinion data through the second web crawler, and takes other points of interest in the same neighboring point of interest set as target points of interest.

The first information updating module 56 uses the preset dialogue template to communicate with the phone number of the target interest point through the AI voice robot, and updates the preset structured information.

And the pause business reminding module 57 is used for supplementing pause business reminding to the display pages of all the interest points in the adjacent interest point set on the network interaction platform when the adjacent interest point set has the interest points exceeding the preset proportion for pausing the business.

The second information updating module 58 calls the phone number of the interest point which is temporarily stopped to operate through the AI voice robot by using the preset dialogue template based on the preset period, and updates the preset structural information of the interest point, wherein the preset structural information at least comprises an address and operating time, and the value range of the preset period is 3 days to 3 months.

The state information publishing system based on the interest points can automatically collect the state information of the interest points, avoid the manpower input, reduce the operation cost and ensure the accuracy of the information published by the network interaction platform.

The above-mentioned embodiments are only preferred examples of the present invention, and are not intended to limit the present invention, and any equivalent substitutions, modifications and changes made within the principle of the present invention are within the protection scope of the present invention.

The embodiment of the invention also provides state information issuing equipment based on the interest points, which comprises a processor. A memory having stored therein executable instructions of the processor. Wherein the processor is configured to perform the steps of the point of interest based state information publication method via execution of executable instructions.

As shown above, the state information publishing system based on the point of interest of the embodiment of the present invention can automatically collect the state information of the point of interest, thereby avoiding human input, reducing operation cost, and ensuring accuracy of information published by the network interaction platform.

As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" platform.

Fig. 4 is a schematic structural diagram of a point-of-interest-based status information distribution apparatus according to the present invention. An electronic device 600 according to this embodiment of the invention is described below with reference to fig. 4. The electronic device 600 shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 4, the electronic device 600 is embodied in the form of a general purpose computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting the different platform components (including the memory unit 620 and the processing unit 610), a display unit 640, etc.

Wherein the storage unit stores program code executable by the processing unit 610 to cause the processing unit 610 to perform steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of the present specification. For example, processing unit 610 may perform the steps as shown in fig. 1.

The storage unit 620 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.

The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 630 may be one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the electronic device 600 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 660. The network adapter 660 may communicate with other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.

The embodiment of the invention also provides a computer-readable storage medium for storing a program, and the program is executed to implement the steps of the state information issuing method based on the points of interest. In some possible embodiments, the aspects of the present invention may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of this specification, when the program product is run on the terminal device.

As shown above, the state information publishing system based on the point of interest of the embodiment of the present invention can automatically collect the state information of the point of interest, thereby avoiding human input, reducing operation cost, and ensuring accuracy of information published by the network interaction platform.

Fig. 5 is a schematic structural diagram of a computer-readable storage medium of the present invention. Referring to fig. 5, a program product 800 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a 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.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A 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 readable storage medium include: an electrical connection having one or more wires, a portable disk, 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.

A computer readable storage medium may include a propagated data signal with 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 readable storage medium may also be any readable medium that is not a 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 readable storage 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.

Program code for carrying out operations for aspects 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, 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 computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

In summary, the present invention is directed to a method, a system, a device and a storage medium for publishing state information based on an interest point, which can automatically collect the state information of the interest point, avoid human input, reduce operation cost, and ensure accuracy of information published by a network interaction platform.

The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.