Streaming media data processing method, device and equipment
阅读说明：本技术 流媒体数据处理方法、装置和设备 (Streaming media data processing method, device and equipment ) 是由 唐一枝 于 2018-08-17 设计创作，主要内容包括：本发明实施例提供一种流媒体数据处理方法、装置和设备,该方法包括：根据流媒体数据的动态特征信息确定对流媒体数据的截取频率。根据此截取频率从流媒体数据中截取出多个数据片段,并识别截取出的多个数据片段各自的数据类型,以得到多个识别结果。根据多个识别结果确定整个流媒体数据的数据类型。在整个确定流媒体数据类型的过程中,流媒体数据的截取频率是根据动态特征信息确定出来的,这使得确定出的截取频率更具有针对性。截取频率不同导致截取出的数据片段的数量也不同,则数据片段识别结果的数量即检测密度也不同。对具有不同动态特征信息的流媒体数据采用不同的检测密度进行检测,从而提高确定出的流媒体数据的数据类型的准确性。(The embodiment of the invention provides a method, a device and equipment for processing streaming media data, wherein the method comprises the following steps: and determining the interception frequency of the streaming media data according to the dynamic characteristic information of the streaming media data. And intercepting a plurality of data segments from the streaming media data according to the interception frequency, and identifying the respective data types of the plurality of intercepted data segments to obtain a plurality of identification results. And determining the data type of the whole streaming media data according to the plurality of identification results. In the whole process of determining the type of the streaming media data, the interception frequency of the streaming media data is determined according to the dynamic characteristic information, so that the determined interception frequency is more targeted. The number of the intercepted data segments is different due to different interception frequencies, and the number of the data segment identification results, namely the detection density, is also different. And detecting the streaming media data with different dynamic characteristic information by adopting different detection densities, thereby improving the accuracy of the determined data type of the streaming media data.)
1. A method for processing streaming media data, comprising:
determining interception frequency according to the dynamic characteristic information of the streaming media data;
intercepting a plurality of data segments from the streaming media data according to the interception frequency;
identifying the respective data types of the plurality of data fragments to obtain a plurality of identification results;
and determining the data type of the streaming media data according to the plurality of identification results.
2. The method of claim 1, wherein the determining the truncation frequency according to the dynamic feature information of the streaming media data comprises:
acquiring first dynamic characteristic information corresponding to the streaming media data when the streaming media data are played to a first time;
determining a first cut-off frequency according to the first dynamic characteristic information;
the intercepting a plurality of data segments from the streaming media data according to the intercepting frequency comprises:
and intercepting the data stream played after the first time according to the first interception frequency to obtain a plurality of first data segments.
3. The method of claim 2, wherein the determining the truncation frequency according to the dynamic feature information of the streaming media data comprises:
acquiring second dynamic characteristic information corresponding to the streaming media data when the streaming media data are played to a second time, wherein the second time is later than the first time;
if the difference degree between the second dynamic characteristic information and the first dynamic characteristic information reaches a preset condition, determining a second interception frequency according to the second dynamic characteristic information;
the intercepting a plurality of data segments from the streaming media data according to the intercepting frequency comprises:
and intercepting the data stream played after the second time according to the second interception frequency to obtain a plurality of second data segments, wherein the first interception frequency is used for intercepting the data stream played from the first time to the second time.
4. The method of claim 3, wherein after determining the second truncation frequency, further comprising:
if the respective data types of the plurality of identified first data fragments meet a preset condition, adjusting the second interception frequency to be a third interception frequency;
the intercepting a plurality of data segments from the streaming media data according to the intercepting frequency comprises:
and intercepting the data stream played after the second time according to the third interception frequency to obtain a plurality of third data segments, wherein the first interception frequency is used for intercepting the data stream played from the first time to the second time.
5. The method of claim 2, wherein the plurality of first data segments are truncated from the data stream played from the first time to the second time, the method further comprising:
if the respective data types of the plurality of identified first data fragments meet a preset condition, adjusting the first interception frequency to be a fourth interception frequency;
and intercepting the data stream played after the second time according to the fourth interception frequency to obtain a plurality of fourth data segments.
6. The method according to claim 4 or 5, wherein the preset conditions comprise: the ratio of the number of data fragments with preset data types in the data types of the first data fragments to the number of the first data fragments is larger than or equal to a preset ratio.
7. The method according to any one of claims 1 to 5, wherein the determining the data type of the streaming media data according to the plurality of recognition results comprises:
counting the number of data segments with preset data types according to the respective data types of the data segments;
and determining whether the data type of the streaming media data is the preset data type according to the ratio of the number of the data segments with the preset data type to the number of the data segments.
8. The method according to any one of claims 1 to 5, wherein after determining the data type of the streaming media data according to the plurality of recognition results, further comprising:
and setting data acquisition permission according to the data type of the streaming media data so as to determine whether the user has the permission to acquire the streaming media data according to the information of the user.
9. A streaming media data processing apparatus, comprising:
the frequency determining module is used for determining interception frequency according to the dynamic characteristic information of the streaming media data;
the intercepting module is used for intercepting a plurality of data fragments from the streaming media data according to the intercepting frequency;
the identification module is used for identifying the respective data types of the plurality of data fragments to obtain a plurality of identification results;
and the type determining module is used for determining the data type of the streaming media data according to the plurality of identification results.
10. An electronic device, comprising: a memory, a processor; wherein the content of the first and second substances,
the memory is used for storing one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the streaming media data processing method according to any one of claims 1 to 8.
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method, an apparatus, and a device for processing streaming media data.
Background
With the continuous development of the internet, people have gradually become accustomed to acquiring streaming media data in an online manner, such as audio resources, video resources or other types of multimedia resources. For a large amount of streaming media data in the internet, sensitive types of streaming media data such as yellow, storm, gambling, poison, etc. are often present. In order to limit the wide spread of these sensitive types of streaming media data, it is necessary to accurately identify them and process them accordingly.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an apparatus, and a device for processing streaming media data, so as to improve accuracy of streaming media data classification, thereby limiting propagation of sensitive streaming media data.
In a first aspect, an embodiment of the present invention provides a streaming media data processing method, including:
determining interception frequency according to the dynamic characteristic information of the streaming media data;
intercepting a plurality of data segments from the streaming media data according to the interception frequency;
identifying the respective data types of the plurality of data fragments to obtain a plurality of identification results;
and determining the data type of the streaming media data according to the plurality of identification results.
In a second aspect, an embodiment of the present invention provides a streaming media data processing apparatus, including:
the frequency determining module is used for determining interception frequency according to the dynamic characteristic information of the streaming media data;
the intercepting module is used for intercepting a plurality of data fragments from the streaming media data according to the intercepting frequency;
the identification module is used for identifying the respective data types of the plurality of data fragments to obtain a plurality of identification results;
and the type determining module is used for determining the data type of the streaming media data according to the plurality of identification results.
In a third aspect, an embodiment of the present invention provides an electronic device, including a processor and a memory, where the memory is configured to store one or more computer instructions, where the one or more computer instructions, when executed by the processor, implement the streaming media data processing method in the first aspect. The electronic device may also include a communication interface for communicating with other devices or a communication network.
In a fourth aspect, an embodiment of the present invention provides a computer storage medium for storing and storing a computer program, where the computer program is used to enable a computer to implement the streaming media data processing method in the first aspect when executed.
The streaming media data processing method provided by the embodiment of the invention determines the interception frequency of the streaming media data according to the dynamic characteristic information of the streaming media data. And intercepting a plurality of data segments from the streaming media data according to the intercepting frequency, and identifying the plurality of intercepted data segments to obtain a plurality of identification results, namely determining the respective data types of the plurality of data segments. And finally, determining the data type of the whole streaming media data according to the respective data types of the plurality of data fragments. The interception frequency of the streaming media data is not uniform throughout the process of determining the data type of the streaming media data. But is determined according to the dynamic characteristic information, so that the determined interception frequency is more targeted. The number of the intercepted data segments is different due to different interception frequencies, and the number of the data segment identification results, that is, the detection density of the streaming media data is also different. The streaming media data with different dynamic characteristic information are detected by adopting different detection densities, so that the accuracy of the determined data type of the streaming media data can be improved. Based on the accurate data type, sensitive streaming media data can be screened from a large amount of streaming media data, and the wide spread of the sensitive streaming media data is limited by processing the sensitive streaming media data.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flowchart of a streaming media data processing method according to an embodiment of the present invention;
fig. 2 is a flowchart of another streaming media data processing method according to an embodiment of the present invention;
fig. 3 is a flowchart of another streaming media data processing method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a streaming media data processing apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device corresponding to the streaming media data processing apparatus provided in the embodiment shown in fig. 4.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and "a" and "an" generally include at least two, but do not exclude at least one, unless the context clearly dictates otherwise.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The words "if," "if," as used herein may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a recognition," depending on the context. Similarly, the phrases "if determined" or "if identified (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when identified (a stated condition or event)" or "in response to an identification (a stated condition or event)", depending on the context.
It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a commodity or system that includes the element.
In addition, the sequence of steps in each method embodiment described below is only an example and is not strictly limited.
Fig. 1 is a flowchart of a streaming media data processing method according to an embodiment of the present invention, where the streaming media data processing method according to the embodiment of the present invention may be executed by a server. As shown in fig. 1, the method comprises the steps of:
s101, determining interception frequency according to the dynamic characteristic information of the streaming media data.
In different scenarios, the streaming media data may be different content. For example, in a live scene, the streaming media data may be a live data stream generated by a host through a host client, and specifically may be a live video stream or a live audio stream. In a common online audio/video playing scenario, the streaming media data may be audio data or video data uploaded to a server by a streaming media data provider, and may be, for example, a movie or a song, etc.
In the process of playing the streaming media data, the server can obtain the dynamic characteristic information of the streaming media data. The dynamic characteristic information of the streaming media data may include multidimensional information such as the number of viewing people, the viewing duration of a viewing user, and a distribution ratio of a location area of the viewing user. Alternatively, when the dynamic feature information includes information of a single dimension, the truncation frequency may be directly determined as the dynamic feature information and the preset parameter 1. When the dynamic characteristic information includes multi-dimensional information, each piece of dimensional information has a corresponding preset parameter, and the interception frequency can be determined according to the information of each dimension in the dynamic characteristic information and the corresponding preset parameter. For example, the interception frequency of the streaming media data is the number of viewers, which is the preset parameter 2+ the proportion of the viewers located in the preset position area, which is the preset parameter 3. The preset position area can be some cities or areas with low security level. The above exemplary interception frequency determination method is a linear determination method, and besides, a non-linear determination method may also be used to determine the interception frequency.
Furthermore, for the dynamic feature information, in addition to the above mentioned dimensions, in a live scene, that is, when the streaming media data is a live data stream, it may further include: number of comments, number of people attended in the live room, etc.
The streaming media data may be a video stream or an audio stream. Therefore, when the streaming media data is an audio stream, the viewing user in the dynamic characteristic information can be understood as a listening user.
S102, intercepting a plurality of data fragments from the streaming media data according to the interception frequency.
S103, identifying the data types of the data fragments to obtain a plurality of identification results.
The server may intercept the streaming media data according to the interception frequency determined in step 101, so as to obtain a plurality of data segments. Since the streaming media data may be a video stream or an audio stream, the data segment captured by the server may be a frame image corresponding to the video stream. The data segment intercepted by the server corresponding to the audio stream may be a frame of audio, that is, a segment of audio segment with a fixed duration, where the fixed duration is about 20-30 ms.
For audio frames and video frames, the server identifies the data types in different ways. Specifically, optionally, a pre-trained classifier may be used to identify the captured image of one frame, so as to obtain a classification result, i.e. a data type of the data segment. Wherein, the classifier which is trained in advance can be adopted in a machine learning mode.
Alternatively, the intercepted audio segment may be recognized using speech recognition techniques to convert the audio segment into text. And further recognizing the characters so as to determine the data type of the audio clip.
And S104, determining the data type of the streaming media data according to the plurality of identification results.
The server can count the number of the data segments corresponding to each data type in the plurality of data segments respectively. Alternatively, the data type having the most data segments may be directly determined as the data type of the streaming media data. Optionally, the data types may include: sensitive or non-sensitive. The sensitive type is usually data segments related to yellow, storm, gambling and poison. The non-sensitive type can be further divided into: inferences, life styles, science fiction, etc. For sensitive type streaming media data, further processing may be performed, such as directly deleting or marking the provider of the sensitive type streaming media data, performing an anchor process and performing an alert process on the anchor, and so on.
In summary, in the embodiment, the interception frequency of the streaming media data is determined according to the dynamic characteristic information of the streaming media data. And intercepting a plurality of data segments from the streaming media data according to the intercepting frequency, and identifying the plurality of intercepted data segments to obtain a plurality of identification results, namely determining the respective data types of the plurality of data segments. And finally, determining the data type of the whole streaming media data according to the respective data types of the plurality of data fragments. The interception frequency of the streaming media data is not uniform throughout the process of determining the data type of the streaming media data. But is determined according to the dynamic characteristic information, so that the determined interception frequency is more targeted. The number of the intercepted data segments is different due to different interception frequencies, and the number of the data segment identification results, that is, the detection density of the streaming media data is also different. The streaming media data with different dynamic characteristic information are detected by adopting different detection densities, so that the accuracy of the determined data type of the streaming media data can be improved. Based on the accurate data type, sensitive type streaming media data can be screened out from a large amount of streaming media data. By processing sensitive types of streaming media data, the wide spread of the streaming media data is limited.
Fig. 2 is a flowchart of another streaming media data processing method according to an embodiment of the present invention, as shown in fig. 2, which may include the following steps:
s201, acquiring first dynamic characteristic information corresponding to the streaming media data played to the first time.
S202, determining a first cutting frequency according to the first dynamic characteristic information.
S203, intercepting the data stream played after the first time according to the first interception frequency to obtain a plurality of first data segments.
When the streaming media data starts to be played, the server does not start to acquire the dynamic feature information. At this time, the stream media data cannot be intercepted and the subsequent data type cannot be determined. When the streaming media data is played to the first time, the server may obtain first dynamic characteristic information corresponding to the first time. Alternatively, the first time may be predetermined and is usually set to a time shorter than the playing time of the streaming media data, for example, 10s after the streaming media data starts playing.
Then, the server determines a first cut-off frequency according to the first dynamic characteristic information corresponding to the first time. The process of determining the clipping frequency can be referred to the related description in the embodiment shown in fig. 1, and is not described herein again. The server intercepts the streaming media data after the first time at the first interception frequency, so as to obtain a plurality of first data segments.
It is worth mentioning here that the streaming media data optionally has other characteristic information in addition to the dynamic characteristic information. Other characteristic information may include a play period of the streaming media data or a type of a provider of the streaming media data, and the like. The type of the provider can be obtained according to the data type of the historical streaming media data provided by the provider. For example, the data type with the largest amount in the historical streaming media is used as the type of the provider. At this time, the server may determine the first truncation frequency by referring to the dynamic characteristic information and the other characteristic information at the same time. And for information of various dimensions in other characteristic information, the information also has corresponding preset parameters.
After determining the first interception frequency, the server may intercept the streaming media data according to the first interception frequency until the streaming media data is played. The intercepted first data segment can be continuously identified while the first data segment is intercepted, so that a plurality of identification results are obtained, and the data type of the streaming media data is determined according to the plurality of identification results.
However, since the first dynamic characteristic information corresponding to the streaming media data at the first time is an instant message, and the first time is usually the time when the streaming media data starts to be played, the first dynamic characteristic information cannot accurately reflect the urgency of the whole streaming media data for determining the data type. Therefore, after the first time, it is often necessary to continuously adjust the interception frequency of the streaming media data, so as to match the interception frequency with the urgency of the streaming media data for data type determination, where the higher the urgency, the higher the interception frequency should be.
In practical applications, the level of the urgency is generally related to the popularity of the streaming media data and the possibility of whether the data type is sensitive. The higher the popularity, the higher the likelihood that the data type is sensitive, and the greater the urgency for making the data type determination.
Based on this, after step 203, the streaming media data processing method may further include the steps of:
and S204, acquiring second dynamic characteristic information corresponding to the streaming media data played to a second time, wherein the second time is later than the first time.
And S205, if the difference between the second dynamic characteristic information and the first dynamic characteristic information reaches a preset condition, determining a second interception frequency according to the second dynamic characteristic information.
S206, intercepting the data stream played after the second time according to the second interception frequency to obtain a plurality of second data segments.
The server may further acquire second dynamic feature information corresponding to a second time when the streaming media is played at a second time while the plurality of first data fragments are intercepted at the first interception frequency, where the second time is later than the first time, and the second time may be preset with a first time interval. At this time, the server may continuously obtain the dynamic feature information with the first time as a starting point and with the preset time duration as a time interval.
The server may compare the second dynamic characteristic information with the first dynamic characteristic information to obtain a difference degree of the dynamic characteristic information. When the difference degree reaches the preset condition, it indicates that the urgency degree of the streaming media data for data type determination at the second time is greatly changed compared with the urgency degree of the streaming media data for data type determination at the first time. At this time, the server may re-determine a second interception frequency according to second dynamic feature information corresponding to the second time. The process of determining the second cut-off frequency is similar to the process of determining the first cut-off frequency, and reference may be made to the related description in the first embodiment, which is not repeated herein.
For the above preset condition, optionally, when the dynamic information feature includes the number of viewers, the preset condition may be: the difference between the number of people watching at the second time and the number of people watching at the first time is larger than a preset threshold value. Optionally, when the dynamic information feature includes a distribution ratio of the location area of the user, the preset condition may further be: the difference between the proportion of the users in the second time preset position area and the proportion of the users in the first time preset position area is larger than the preset proportion.
After the second interception frequency is obtained, the server intercepts the streaming media data played after the second time according to the second interception frequency to obtain a plurality of second data segments.
The process of the server intercepting the streaming media data by using the first interception frequency and the second interception frequency can be understood as follows: the server intercepts streaming media data played between a first time and a second time at a first interception frequency to obtain a plurality of first data segments; and intercepting the streaming media data played after the second time by a second interception frequency to obtain a plurality of second data segments.
S207, identifying the respective data types of the plurality of first data fragments and the plurality of second data fragments to obtain a plurality of identification results.
The server identifies the first data segment and the second data segment as captured to obtain their respective data types. For a specific data type identification process, reference may be made to the related description in the first embodiment, and details are not described herein again.
It should be noted that the identification processes of the first data segment and the second data segment may also be performed asynchronously. In practical application, the server can identify the plurality of first data fragments after intercepting the plurality of first data fragments, and can determine a second interception frequency while identifying the plurality of first data fragments.
And S208, determining the data type of the streaming media data according to the plurality of identification results.
After determining that the respective data types of the plurality of first data segments and the plurality of second data segments are the plurality of identification results, in an optional manner, the server may count the total number of the first data segments and the second data segments and the number of data segments with the preset data type in the plurality of data segments, and calculate a ratio of the number of data segments with the preset data type to the total number of data segments. And if the ratio is larger than a preset threshold value, determining that the data type of the streaming media data is a preset data type. The preset data type may be a sensitive type.
In the above steps 201-208, the interception frequency is continuously adjusted by using the dynamic characteristic information. In practical application, the interception frequency can be continuously adjusted by simultaneously combining the dynamic characteristic information and the identified data type of each first data segment, so as to further improve the matching degree of the interception frequency and the urgency degree of the streaming media data for determining the data type. Therefore, after step 205, optionally, the streaming media data processing method may further include the steps of:
(1) and if the data types corresponding to the plurality of identified first data segments meet the preset condition, adjusting the second interception frequency to be a third interception frequency.
Specifically, the server identifies first data segments that are truncated at a first truncation frequency to obtain a data type for each first data segment. And if the data types respectively corresponding to the plurality of first data fragments meet the preset condition, determining to adjust the second interception frequency to be a third interception frequency. Optionally, the preset condition may include: the ratio of the number of data fragments with preset data types in the data types of the first data fragments to the number of the first data fragments is larger than or equal to a preset ratio.
Since the second truncation frequency is determined according to the second dynamic characteristics information, the third truncation frequency obtained by adjusting the second truncation frequency can be understood as being obtained according to the second dynamic characteristics information and the data types respectively corresponding to the plurality of first data segments. For example, the third clipping frequency is the second dynamic characteristic information 4+ the ratio 5. The preset parameters 1 to 5 related to the present embodiment and the above embodiments may be equal or different.
(2) The server may intercept the data stream played after the second time according to a third interception frequency to obtain a plurality of third data segments.
At this time, the interception of the streaming media data by the server can be understood as: intercepting streaming media data played between a first time and a second time at a first interception frequency to obtain a plurality of first data segments; and intercepting the streaming media data played after the second time by using a third interception frequency so as to obtain a plurality of third data segments. The server can identify the first data segment and the third data segment to obtain a plurality of identification results. And determining the data type of the streaming media data according to the plurality of identification results.
In this embodiment, in one mode, the server determines a first interception frequency according to first dynamic feature information corresponding to a first time and intercepts a plurality of first data fragments, determines a second interception frequency according to second dynamic feature information corresponding to a second time, and intercepts a plurality of second data fragments by using the second interception frequency. This method adjusts the clipping frequency according to the dynamically changing dynamic characteristic information. In another mode, after obtaining a plurality of first data fragments, the server identifies the first data fragments and obtains second dynamic feature information. And then, adjusting the interception frequency according to the identified data type of each first data fragment and the second dynamic characteristic information. Namely, the interception frequency is adjusted according to the identification result of the data segment and the dynamic characteristic information. In the process of playing the streaming media data, the two adjustment modes of the interception frequency can continuously change the detection density of the streaming media data so as to improve the accuracy of the determined data type of the streaming media data.
Fig. 3 is a flowchart of another streaming media data processing method according to an embodiment of the present invention, and as shown in fig. 3, the streaming media data processing method may further include the following steps:
s301, acquiring first dynamic characteristic information corresponding to the streaming media data played to the first time.
S302, determining a first cut-off frequency according to the first dynamic characteristic information.
S303, intercepting the data stream played after the first time according to the first interception frequency to obtain a plurality of first data segments.
The execution process of the above steps 301 to 303 is similar to the corresponding steps of the foregoing embodiment, and reference may be made to the related description in the embodiment shown in fig. 2, which is not repeated herein.
S304, if the data types corresponding to the identified first data segments respectively satisfy the preset condition, adjusting the first interception frequency to be a fourth interception frequency, where the intercepted first data segments are intercepted from the data stream played from the first time to the second time.
S305, truncating the data stream played after the second time according to a fourth truncation frequency to obtain a plurality of fourth data segments.
After the plurality of first data segments are obtained, the server can judge whether the data types corresponding to the plurality of first data segments respectively meet preset conditions or not, and determine whether to adjust the first interception frequency or not according to the judgment result. And if the data types respectively corresponding to the plurality of first data segments meet the preset condition, adjusting the first interception frequency to be a fourth interception frequency. Optionally, the preset condition here is the same as that in the second embodiment: the ratio of the number of the preset data types existing in the data types respectively corresponding to the first data segments to the number of the first data segments is greater than or equal to the preset ratio. And the fourth clipping frequency is greater than the first clipping frequency. It can be seen that the first clipping frequency is adjusted to the fourth clipping frequency by using the data types corresponding to the plurality of first data segments, i.e. the identification results of the plurality of first data segments. Then, the server may intercept the streaming media data played after the second time according to the fourth interception frequency to obtain a plurality of fourth data segments.
S306, identifying the respective data types of the first data fragments and the fourth data fragments to obtain a plurality of identification results.
S307, determining the data type of the streaming media data according to the plurality of identification results.
The execution process of the
In this embodiment, after obtaining the first interception frequency and the plurality of first data segments, the server may adjust the interception frequency according to the data type of each identified first data segment. Namely, the interception frequency of the streaming media data is adjusted according to the identification result of the first data segment. In the process of playing the streaming media data, the detection density of the streaming media data is continuously changed by continuously adjusting the interception frequency, and finally the accuracy of the determined data type of the streaming media data can be improved.
In addition, after determining the data type of the streaming media data by using the methods provided by the embodiments, the server may also set a corresponding data acquisition right for the streaming media data according to the data type. For example, viewing is prohibited under 18 years of age, etc. When the user wants to acquire the streaming media data, the server responds to a click watching operation triggered by the user to acquire information of the user, such as gender, age and the like, compares the information of the user with the data acquisition permission and determines whether the user can acquire the streaming media data, so that the purpose of guiding different users to watch corresponding streaming media data is finally achieved, and the wide spread of sensitive streaming media data is avoided to the greatest extent.
The streaming media data processing apparatus according to one or more embodiments of the present invention will be described in detail below. Those skilled in the art will appreciate that these streaming media data processing devices can be configured using commercially available hardware components through the steps taught in this scheme.
Fig. 4 is a schematic structural diagram of a streaming media data processing apparatus according to an embodiment of the present invention, as shown in fig. 4, the apparatus includes: a
And the
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The identifying
A
Optionally, the
The obtaining
A determining
The intercepting
Optionally, the obtaining
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Optionally, the apparatus further comprises: and an
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Optionally, the apparatus further comprises: a
The
The apparatus shown in fig. 4 can perform the method of the embodiment shown in fig. 1 to 3, and reference may be made to the related description of the embodiment shown in fig. 1 to 3 for a part not described in detail in this embodiment. The implementation process and technical effect of the technical solution refer to the descriptions in the embodiments shown in fig. 1 to fig. 3, and are not described herein again.
The internal functions and structures of the streaming media data processing apparatus are described above, and in one possible design, the structure of the streaming media data processing apparatus may be implemented as an electronic device, which may be a server carrying streaming media data that can be acquired by a wide range of users, as shown in fig. 5, and the electronic device may include: a
The program comprises one or more computer instructions which, when executed by the
determining interception frequency according to the dynamic characteristic information of the streaming media data;
intercepting a plurality of data segments from the streaming media data according to the interception frequency;
identifying the respective data types of the plurality of data fragments to obtain a plurality of identification results;
and determining the data type of the streaming media data according to the plurality of identification results.
Optionally, the
The electronic device may further include a
In addition, an embodiment of the present invention provides a computer storage medium for storing computer software instructions for the electronic device, which includes a program for executing the method for identifying streaming media data processing in the method embodiments shown in fig. 1 to fig. 3.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course, can also be implemented by a combination of hardware and software. With this understanding in mind, the above-described aspects and portions of the present technology which contribute substantially or in part to the prior art may be embodied in the form of a computer program product, which may be embodied on one or more computer-usable storage media having computer-usable program code embodied therein, including without limitation disk storage, CD-ROM, optical storage, and the like.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
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