CN113177160A - Pushed document generation method and device, electronic equipment and storage medium - Google Patents
Pushed document generation method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN113177160A CN113177160A CN202110571716.7A CN202110571716A CN113177160A CN 113177160 A CN113177160 A CN 113177160A CN 202110571716 A CN202110571716 A CN 202110571716A CN 113177160 A CN113177160 A CN 113177160A
- Authority
- CN
- China
- Prior art keywords
- information
- pushed
- target user
- keyword information
- keyword
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 47
- 230000000694 effects Effects 0.000 claims abstract description 29
- 238000012216 screening Methods 0.000 claims description 22
- 230000006870 function Effects 0.000 claims description 18
- 238000004891 communication Methods 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 10
- 238000004422 calculation algorithm Methods 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 238000010586 diagram Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 8
- 230000009471 action Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 3
- 238000001914 filtration Methods 0.000 description 3
- 238000012549 training Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 230000002354 daily effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/186—Templates
Abstract
The embodiment of the invention provides a method, a device, electronic equipment and a storage medium for generating a pushed document, which are applied to the technical field of information and are used for acquiring information to be pushed of a target user; determining keyword information of information to be pushed and keyword information of interest preference of a target user; matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user; and generating a to-be-pushed document according to the matched keyword information, and pushing the to-be-pushed document to the target user. The corresponding file can be generated according to the keyword information of the interest preference of the user for different users and sent to the user, so that the technical problem of poor user experience effect caused by single file form in the prior art is solved, and the user experience effect is improved.
Description
Technical Field
The present invention relates to the field of information technologies, and in particular, to a method and an apparatus for generating a push document, an electronic device, and a storage medium.
Background
With the popularization of mobile intelligent terminal devices and the rapid development of mobile applications, users often browse information such as news and videos through intelligent terminals. Meanwhile, in order to improve the experience effect of the user, each application often pushes hotspot information to the user in a mode of generating and sending a push file, so that the user can browse conveniently.
However, at present, when information is pushed, an application program often pushes the same popular video content to all users, the format of the pushed title file is relatively uniform, and after the user receives the type of pushing for a long time, the freshness of the user for pushing is slowly reduced, so that the user experience effect is poor.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a device for generating a pushed document, electronic equipment and a storage medium, so as to achieve the purpose of improving the experience effect of a user for receiving the pushed document. The specific technical scheme is as follows:
in a first aspect of the present invention, there is provided a method for generating a pushed document, where the method includes:
acquiring information to be pushed of a target user;
determining keyword information of information to be pushed and keyword information of interest preference of a target user;
matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user;
and generating a to-be-pushed document according to the matched keyword information, and pushing the to-be-pushed document to the target user.
Optionally, generating a document to be pushed according to the matched keyword information, and pushing the document to be pushed to the target user, including:
searching a corresponding preset document generation template through the keyword information with the interest preference according to the preset mapping relation between the keyword information with the interest preference and the document generation template;
and generating a to-be-pushed document according to the matched keyword information by using a preset document generation template, and pushing the to-be-pushed document to the target user.
Optionally, generating a document to be pushed according to the matched keyword information, and pushing the document to be pushed to the target user, further comprising:
generating a document to be pushed according to the matched keyword information;
acquiring and establishing an active time probability function corresponding to a target user according to a historical record of the target user;
calculating a time period with the maximum target user activity probability as the active time period of the target user according to the active time probability function;
and pushing the file to be pushed to the target user in the active time period.
Optionally, matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user, including:
and matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information which is the same as the keyword information of the information to be pushed in the keyword information of each interest preference of the target user and is used as the matched keyword information.
Optionally, the obtaining of the information to be pushed of the target user includes:
calculating to obtain the keyword information of each interest preference of the target user according to the history of the target user through a multi-dimensional user portrait interest model;
acquiring keyword information of each information in an information base to be pushed;
matching the keyword information of each interest preference of the target user with the keyword information of each information in the information base to be pushed, and selecting the information in the corresponding information base to be pushed with the highest matching degree as the information to be pushed.
Optionally, obtaining the keyword information of each information in the information base to be pushed includes
Acquiring information screened according to a preset screening rule and/or information uploaded by a target user;
acquiring and sequencing according to information screened according to a preset screening rule and/or updating time of information uploaded by a target user;
and acquiring the information screened according to a preset screening rule and/or the keyword information of the first N pieces of information with latest update time in the information uploaded by the target user.
Optionally, the obtaining of the keyword information of each interest preference of the target user through the multidimensional user portrait interest model and calculation according to the history of the target user includes:
acquiring a historical browsing record and/or a historical watching record of a target user;
and inputting the historical browsing record and/or the historical watching record of the target user into a pre-trained multi-dimensional user image interest model, and calculating to obtain the keyword information of each interest preference of the target user.
Optionally, matching the keyword information of each interest preference of the target user with the keyword information of each information in the information base to be pushed, and selecting the information in the information base to be pushed with the highest corresponding matching degree as the information to be pushed, including:
inputting the keyword information of each interest preference of the target user and the keyword information of each information in the information base to be pushed into a pre-trained algorithm prediction model to obtain the matching degree score of the keyword information of each interest preference and the keyword information of each information in the information base to be pushed;
and selecting the information in the information base to be pushed with the highest matching degree as the information to be pushed.
In a second aspect of the present invention, there is also provided a pushed document generation apparatus, including:
the information to be pushed acquisition module is used for acquiring information to be pushed of a target user;
the keyword information determining module is used for determining keyword information of information to be pushed and keyword information of interest preference of a target user;
the keyword information matching module is used for matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user;
and the to-be-pushed document generation module is used for generating a to-be-pushed document according to the matched keyword information and pushing the to-be-pushed document to the target user.
Optionally, the document generation module to be pushed includes:
the template searching submodule is used for searching a corresponding preset file generation template through the keyword information with the interest preference according to the mapping relation between the preset keyword information with the interest preference and the file generation template;
and the document pushing submodule is used for generating a document to be pushed according to the matched keyword information by using a preset document generating template, and pushing the document to be pushed to the target user.
Optionally, the document generation module to be pushed further includes:
the pattern generation submodule is used for generating a pattern to be pushed according to the matched keyword information;
the probability function creating submodule is used for acquiring and creating an active time probability function corresponding to a target user according to the historical record of the target user;
the active time period calculation submodule is used for calculating a time period with the maximum active probability of the target user according to the active time probability function and taking the time period as the active time period of the target user;
and the file pushing submodule is used for pushing the file to be pushed to the target user in the active time period.
Optionally, the keyword information matching module is specifically configured to: and matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information which is the same as the keyword information of the information to be pushed in the keyword information of each interest preference of the target user and is used as the matched keyword information.
Optionally, the information to be pushed obtaining module includes:
the interest preference calculation sub-module is used for calculating and obtaining the keyword information of each interest preference of the target user according to the history of the target user through the multi-dimensional user portrait interest model;
the keyword information acquisition submodule is used for acquiring the keyword information of each information in the information base to be pushed;
and the information to be pushed selecting submodule is used for matching the keyword information of each interest preference of the target user with the keyword information of each piece of information in the information base to be pushed, and selecting the information in the information base to be pushed with the highest corresponding matching degree as the information to be pushed.
Optionally, the keyword information obtaining sub-module comprises
The screening and uploading information acquisition submodule is used for acquiring information screened according to a preset screening rule and/or information uploaded by a target user;
the screening and uploading information sorting submodule is used for acquiring and sorting the information screened according to the preset screening rule and/or the updating time of the information uploaded by the target user;
and the screening and uploading information selection submodule is used for acquiring the information screened according to the preset screening rule and/or the keyword information of the first N pieces of information with latest updating time in the information uploaded by the target user.
Optionally, the interest preference calculating sub-module includes:
the browsing and viewing record acquisition submodule is used for acquiring a historical browsing record and/or a historical viewing record of a target user;
and the interest preference keyword acquisition sub-module is used for inputting the historical browsing record and/or the historical watching record of the target user into a pre-trained multi-dimensional user image interest model and calculating to obtain the keyword information of each interest preference of the target user.
Optionally, the to-be-pushed information selection sub-module includes:
the matching degree score calculating sub-module is used for inputting the keyword information of each interest preference of the target user and the keyword information of each information in the information base to be pushed into an algorithm prediction model obtained by pre-training to obtain the matching degree score of the keyword information of each interest preference and the keyword information of each information in the information base to be pushed;
and the highest matching degree selecting submodule is used for selecting the information in the information base to be pushed with the highest matching degree as the information to be pushed.
In yet another aspect of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements any one of the above-mentioned push-document generating methods.
In yet another aspect of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform any of the above-mentioned push document generation methods.
The embodiment of the invention provides a method, a device, electronic equipment and a storage medium for generating a pushed document, which are used for acquiring information to be pushed of a target user; determining keyword information of information to be pushed and keyword information of interest preference of a target user; matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user; and generating a to-be-pushed document according to the matched keyword information, and pushing the to-be-pushed document to the target user. The corresponding file can be generated according to the keyword information of the interest preference of the user for different users and sent to the user, so that the technical problem of poor user experience effect caused by single file form in the prior art is solved, and the user experience effect is improved.
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.
Fig. 1 is a first flowchart of a pushed document generation method according to an embodiment of the present application;
FIG. 2a is a diagram of a first example of a push document according to an embodiment of the present application;
FIG. 2b is a diagram of a second example of a push document according to an embodiment of the present application;
FIG. 2c is a diagram of a third example of a push document according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of pushing to a user according to an embodiment of the present application;
fig. 4 is a schematic flowchart of a process of acquiring information to be pushed of a target user according to an embodiment of the present application;
FIG. 5 is a diagram illustrating an example of a method for generating a push document according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a push document generating apparatus according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.
In order to improve the experience effect of a user for receiving a pushed document, the embodiment of the application provides a pushed document generating method.
In one embodiment of the present application, the method includes:
acquiring information to be pushed of a target user;
determining keyword information of information to be pushed and keyword information of interest preference of a target user;
matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user;
and generating a to-be-pushed document according to the matched keyword information, and pushing the to-be-pushed document to the target user.
Therefore, by the method for generating the pushed document, the corresponding document can be generated according to the keyword information of the interest preference of the user for different users and sent to the user, the technical problem of poor user experience effect caused by single document form in the prior art is solved, and the user experience effect is improved.
The following describes in detail the push document generation method provided in the embodiments of the present application with specific embodiments.
The push document in the embodiment of the application can be generated when the application sends push information to a user, and the user can know the information generated after interest and preference through the push document. For example, when a certain chinese song is pushed to a user, the pushed document is: guessing you like Chinese music.
Specifically, referring to fig. 1, fig. 1 is a first flowchart of a method for generating a push document according to an embodiment of the present application, including:
and step S11, acquiring the information to be pushed of the target user.
The target user may be all or a portion of the users in the current user group. In the actual use process, a user who installs the current application and starts the information push function can be selected from the current user group as a target user. For example, the current user population of the application is initially filtered out, filtering out users whose push notifications are closed and users who uninstall the application. By selecting the target user from the current user group, the effectiveness of information pushing can be improved, and the invalid pushing amount is reduced.
The information to be pushed may be information obtained by matching according to the interest preference of the target user. For example, by obtaining the keyword information of interest preference of the target user, matching the keyword information of interest preference with the keyword information of each information in the information base to be pushed, and using the information in the information base to be pushed obtained by matching as the information to be pushed. In the actual use process, the keyword information of the interest preference of the target user can be obtained through the multi-dimensional user portrait interest model according to the historical records of the user. The information in the information base to be pushed may be information that is pre-screened and/or information that is uploaded by a target user. For example, the uploaded information may be manually filtered to screen out popular information and target information uploaded by a target user, where the target user may be a predetermined specified user, such as a popular upload user with more fans.
The method for generating the push document in the embodiment of the application can be executed through an intelligent terminal, and the intelligent terminal can be a computer or a server.
And step S12, determining the keyword information of the information to be pushed and the keyword information of the interest preference of the target user.
Determining the keyword information of the information to be pushed can acquire the keyword information of the related information such as the name, author and the like of each information in the information library to be pushed. For example, when each piece of information in the information library to be pushed is video information, a title content tag, a video type tag, uploading personnel information, a video embedding vector, and the like of the video can be acquired.
The interest preference keyword information of the target user is determined, and the interest preference keyword information of the tag interest of the target user, the interest preference keyword information of the channel category, the interest preference keyword information of the uploading personnel and the single video preference keyword information can be obtained through calculation according to the history of the target user by the multi-dimensional user image interest model.
Step S13, matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user, to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user.
The keyword information of the information to be pushed is matched with the keyword information of each interest preference of the target user, the keyword information of the information to be pushed and the keyword information of each interest preference of the target user can be input into a pre-trained prediction model for prediction, and the matching degree score between the keyword information of the information to be pushed and the keyword information of each interest preference of the target user is obtained. The prediction model may be various models for performing matching degree calculation, such as an FM (factor decomposition Machine) model algorithm.
Obtaining keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user, and selecting the keyword information with the matching degree score larger than a preset threshold value as the matched keyword information according to the matching degree score between the keyword information of the information to be pushed and the keyword information of each interest preference of the target user. Or selecting the keyword information with the maximum matching degree score as the matched keyword information according to the matching degree score between the keyword information of the information to be pushed and the keyword information of each interest preference of the target user.
Optionally, in an actual use process, matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user, and selecting the keyword information, which is the same as the keyword information of the information to be pushed, in the keyword information of each interest preference of the target user as the matched keyword information.
And step S14, generating a to-be-pushed case according to the matched keyword information, and pushing the to-be-pushed case to the target user.
Optionally, generating a document to be pushed according to the matched keyword information, and pushing the document to be pushed to the target user, including: searching a corresponding preset document generation template through the keyword information with the interest preference according to the preset mapping relation between the keyword information with the interest preference and the document generation template; and generating a to-be-pushed document according to the matched keyword information by using a preset document generation template, and pushing the to-be-pushed document to the target user.
The to-be-pushed case is generated according to the matched keyword information, the corresponding case can be selected according to the type of the matched keyword information, for example, the type of the keyword information is a name, a song type, an author and the like, and the corresponding case is selected according to the type of the keyword information.
For example, referring to fig. 2a, fig. 2a is a diagram of a first example of the present application, and if the matched keyword information is a tag "× (name)", it may be determined that the target user has an interest preference for the tag "×", so that a corresponding "guess you pay attention" × "may be generated for the target user instead of the" hot spot ".
For another example, referring to fig. 2b, fig. 2b is a diagram of a second example of the pushed scripture according to the embodiment of the present application, and if the matched keyword information indicates that the song category is "chinese music", a pushed scripture of "guessing you focus on chinese music" may be generated for the target user.
For another example, referring to fig. 2c, fig. 2c is a diagram of a third example of a push document in the embodiment of the present application, and if the matched keyword information is a certain uploading user, a "person you are interested in updates" push document may be generated for the target user.
Therefore, by the method for generating the pushed document, the corresponding document can be generated according to the keyword information of the interest preference of the user for different users and sent to the user, the technical problem of poor user experience effect caused by single document form in the prior art is solved, and the user experience effect is improved.
Optionally, referring to fig. 3, step S14 is to generate a document to be pushed according to the matched keyword information, and push the document to be pushed to the target user, further including:
and step S141, generating a document to be pushed according to the matched keyword information.
And step S142, acquiring and establishing an active time probability function corresponding to the target user according to the historical record of the target user.
And step S143, calculating a time period with the maximum target user activity probability according to the activity time probability function, and using the time period as the target user activity time period.
And step S144, pushing the file to be pushed to the target user in the active time period.
Specifically, an active time probability function corresponding to the target user may be established, and the active probability of each time period is obtained through a statistical method according to the history of the target user. For example, through statistics, the user browses 100 times in the past week, and the browsing times from 20 to 21 points are 30 times, so that the activity probability of the user from 20 to 21 points is 30%, and the browsing times in each time period are counted in sequence to obtain the activity probability of each time period.
And calculating a time period with the maximum target user activity probability as the target user activity time period according to the activity time probability function, and pushing the file to be pushed to the target user in the activity time period. For example, when the activity probability of each time period in one day is counted, and the activity probability from 20 to 21 points of the target user is obtained to be the maximum, the 20 to 21 points may be used as the activity time period to push the to-be-pushed file to the target user.
Therefore, an active time probability function corresponding to the target user is established by acquiring and according to the historical record of the target user, and the file to be pushed is pushed to the target user in the active time period. The probability of the target user receiving the pushed document can be improved, and the document pushing efficiency is improved.
Optionally, referring to fig. 4, the step S11 obtains the information to be pushed of the target user, including:
and step S111, calculating and obtaining the keyword information of each interest preference of the target user according to the history of the target user through the multi-dimensional user portrait interest model.
Optionally, the obtaining of the keyword information of each interest preference of the target user through the multidimensional user portrait interest model and calculation according to the history of the target user includes: acquiring a historical browsing record and/or a historical watching record of a target user; and inputting the historical browsing record and/or the historical watching record of the target user into a pre-trained multi-dimensional user image interest model, and calculating to obtain the keyword information of each interest preference of the target user.
The history may include browsing and viewing records. Specifically, the browsing and viewing records may include browsing time, browsed information, and the like. For example, the user viewed a television series, 12/2020/20: 28-12/2020/21: 01.
Optionally, a multi-dimensional user image interest model is established by using browsing and viewing history records of the target user in the application, the target user preference for tag interest, the channel category interest preference, the uploader interest preference, the single video preference and the like are described from multiple dimensions, and the preference degrees of the target user preference, the channel category interest preference, the uploader interest preference, the single video preference and the like are expressed by scores; meanwhile, according to the daily user behaviors, updating each dimension interest preference score of the user, maintaining the dynamic updating of the user portrait interest model, and adding time attenuation, if the user has a certain interest preference score but does not perform related historical record behaviors for a long time, the interest point preference score is reduced.
Step S112, obtaining the keyword information of each information in the information base to be pushed.
Optionally, obtaining keyword information of each information in the information library to be pushed includes: acquiring information screened according to a preset screening rule and/or information uploaded by a target user; acquiring and sequencing according to information screened according to a preset screening rule and/or updating time of information uploaded by a target user; and acquiring the information screened according to a preset screening rule and/or the keyword information of the first N pieces of information with latest update time in the information uploaded by the target user.
Step S113, matching the keyword information of each interest preference of the target user with the keyword information of each information in the information base to be pushed, and selecting the information in the corresponding information base to be pushed with the highest matching degree as the information to be pushed.
Optionally, matching the keyword information of each interest preference of the target user with the keyword information of each information in the information base to be pushed, and selecting the information in the information base to be pushed with the highest corresponding matching degree as the information to be pushed, including: inputting the keyword information of each interest preference of the target user and the keyword information of each information in the information base to be pushed into a pre-trained algorithm prediction model to obtain the matching degree score of the keyword information of each interest preference and the keyword information of each information in the information base to be pushed; and selecting the information in the information base to be pushed with the highest matching degree as the information to be pushed.
Therefore, the keyword information of each interest preference of the target user is obtained through calculation according to the history of the target user, the keyword information of each interest preference of the target user is matched with the keyword information of each information in the information base to be pushed, and the information in the information base to be pushed with the highest corresponding matching degree is selected as the information to be pushed. The file corresponding to the pushed video can be generated according to the interest preference information of different users and sent to the users.
Referring to fig. 5, fig. 5 is a diagram of an example of a method for generating a push document according to an embodiment of the present application, including:
1. and selecting candidate videos, marking the videos to be pushed in a video library with marks to be pushed through manual screening, and meanwhile, automatically marking the marks to be pushed by the videos of the uploaders set as the white list. And selecting the latest twenty thousand videos as candidate push videos every day.
2. And (4) defining candidate groups, selecting a user group which opens the mobile application recently, performing preliminary filtering on the user group, filtering out users who push the notification to be closed and users who unload the application, and reducing invalid pushing amount.
3. And (4) video feature generation, namely selecting a title content label, a video type label, an uploader, a video embedding vector and the like of the candidate video as features of the video side.
4. The user portrait interest generation method includes the steps of establishing a multi-dimensional user portrait interest model by means of browsing and watching historical records of a user in an application, describing interest preference of the user on labels, interest preference of channel categories, interest preference of uploaders, single video preference and the like from multiple dimensions, representing preference degrees of the user with scores, adding time interest attenuation and maintaining dynamic updating of the user portrait interest model.
5. And generating a user push list, matching the multi-dimensional interest of each user with the corresponding video characteristics, inputting a pre-trained sequencing model to obtain the matching score of each user for each video to be pushed, and selecting the video with the highest score as the final push video.
6. And generating a user push file, and after obtaining the video to be pushed of each user in the personalized video push channel, inquiring which interest preference of the user is matched and recalled for the pushed video. According to the source of the video recall, personalized pushed documents can be matched for users. For the generation relation between the pushed case and the video to be pushed by the user, a case type database is maintained, and the database comprises the mapping relation between a case template and a pushed video source. After generating the personalized push video for the user, searching the corresponding push file template by inquiring the matching source of the video to be pushed and the user interest, and generating the personalized push file for each user.
7. And after the user is matched with the video, a personalized active time probability function is established for each user by utilizing the time record of the historical behavior data of the user in the application, and the video is transmitted to the user side within the active time period with the maximum probability of the user, so that the transmission time is dispersed, the probability of disturbing the user is reduced as much as possible, and the pushing effect is improved.
In a second aspect implemented by the present invention, there is also provided a push document generation apparatus, referring to fig. 6, the apparatus including:
the information to be pushed acquiring module 601 is configured to acquire information to be pushed of a target user;
a keyword information determining module 602, configured to determine keyword information of information to be pushed and keyword information of interest preference of a target user;
the keyword information matching module 603 is configured to match the keyword information of the information to be pushed with the keyword information of each interest preference of the target user, so as to obtain keyword information, which is matched with the keyword information of the information to be pushed, in the keyword information of each interest preference of the target user;
and a to-be-pushed document generating module 604, configured to generate a to-be-pushed document according to the matched keyword information, and push the to-be-pushed document to the target user.
Optionally, the to-be-pushed document generating module 604 includes:
the template searching submodule is used for searching a corresponding preset file generation template through the keyword information with the interest preference according to the mapping relation between the preset keyword information with the interest preference and the file generation template;
and the document pushing submodule is used for generating a document to be pushed according to the matched keyword information by using a preset document generating template, and pushing the document to be pushed to the target user.
Optionally, the to-be-pushed document generating module 604 further includes:
the pattern generation submodule is used for generating a pattern to be pushed according to the matched keyword information;
the probability function creating submodule is used for acquiring and creating an active time probability function corresponding to a target user according to the historical record of the target user;
the active time period calculation submodule is used for calculating a time period with the maximum active probability of the target user according to the active time probability function and taking the time period as the active time period of the target user;
and the file pushing submodule is used for pushing the file to be pushed to the target user in the active time period.
Optionally, the keyword information matching module 603 is specifically configured to: and matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information which is the same as the keyword information of the information to be pushed in the keyword information of each interest preference of the target user and is used as the matched keyword information.
Optionally, the to-be-pushed information obtaining module 601 includes:
the interest preference calculation sub-module is used for calculating and obtaining the keyword information of each interest preference of the target user according to the history of the target user through the multi-dimensional user portrait interest model;
the keyword information acquisition submodule is used for acquiring the keyword information of each information in the information base to be pushed;
and the information to be pushed selecting submodule is used for matching the keyword information of each interest preference of the target user with the keyword information of each piece of information in the information base to be pushed, and selecting the information in the information base to be pushed with the highest corresponding matching degree as the information to be pushed.
Optionally, the keyword information obtaining sub-module comprises
The screening and uploading information acquisition submodule is used for acquiring information screened according to a preset screening rule and/or information uploaded by a target user;
the screening and uploading information sorting submodule is used for acquiring and sorting the information screened according to the preset screening rule and/or the updating time of the information uploaded by the target user;
and the screening and uploading information selection submodule is used for acquiring the information screened according to the preset screening rule and/or the keyword information of the first N pieces of information with latest updating time in the information uploaded by the target user.
Optionally, the interest preference calculating sub-module includes:
the browsing and viewing record acquisition submodule is used for acquiring a historical browsing record and/or a historical viewing record of a target user;
and the interest preference keyword acquisition sub-module is used for inputting the historical browsing record and/or the historical watching record of the target user into a pre-trained multi-dimensional user image interest model and calculating to obtain the keyword information of each interest preference of the target user.
Optionally, the to-be-pushed information selection sub-module includes:
the matching degree score calculating sub-module is used for inputting the keyword information of each interest preference of the target user and the keyword information of each information in the information base to be pushed into an algorithm prediction model obtained by pre-training to obtain the matching degree score of the keyword information of each interest preference and the keyword information of each information in the information base to be pushed;
and the highest matching degree selecting submodule is used for selecting the information in the information base to be pushed with the highest matching degree as the information to be pushed.
Therefore, through the push filing generation device provided by the embodiment of the application, the corresponding filing can be generated according to the keyword information of the interest preference of the user and sent to the user aiming at different users, the technical problem of poor user experience effect caused by single filing form in the prior art is solved, and the user experience effect is improved.
An embodiment of the present invention further provides an electronic device, as shown in fig. 7, including a processor 701, a communication interface 702, a memory 703 and a communication bus 704, where the processor 701, the communication interface 702, and the memory 703 complete mutual communication through the communication bus 704,
a memory 703 for storing a computer program;
the processor 701 is configured to implement the following steps when executing the program stored in the memory 703:
acquiring information to be pushed of a target user;
determining keyword information of information to be pushed and keyword information of interest preference of a target user;
matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user;
and generating a to-be-pushed document according to the matched keyword information, and pushing the to-be-pushed document to the target user.
The communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the terminal and other equipment.
The Memory may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In another embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored, and the computer program, when executed by a processor, implements the push document generation method described in any of the above embodiments.
In another embodiment of the present invention, there is also provided a computer program product containing instructions, which when run on a computer, causes the computer to execute the method for generating a push document as described in any of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus, the electronic device, the storage medium, and the computer program product embodiment, since they are substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to part of the description of the method embodiment.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (11)
1. A method for generating a pushed document, the method comprising:
acquiring information to be pushed of a target user;
determining the keyword information of the information to be pushed and the keyword information of the interest preference of the target user;
matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user;
and generating a to-be-pushed document according to the matched keyword information, and pushing the to-be-pushed document to the target user.
2. The method according to claim 1, wherein the generating a document to be pushed according to the matched keyword information and pushing the document to be pushed to the target user comprises:
searching a corresponding preset document generation template through the keyword information with the interest preference according to the mapping relation between the keyword information with the preset interest preference and the document generation template;
and generating a to-be-pushed file according to the matched keyword information through the preset file generation template, and pushing the to-be-pushed file to the target user.
3. The method according to claim 1, wherein the generating a document to be pushed according to the matched keyword information and pushing the document to be pushed to the target user further comprises:
generating a document to be pushed according to the matched keyword information;
acquiring and establishing an active time probability function corresponding to the target user according to the historical record of the target user;
calculating to obtain a time period with the maximum target user activity probability as the active time period of the target user according to the active time probability function;
and pushing the file to be pushed to the target user in the active time period.
4. The method according to claim 1, wherein the matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information of each interest preference of the target user, which is matched with the keyword information of the information to be pushed, comprises:
and matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information which is the same as the keyword information of the information to be pushed in the keyword information of each interest preference of the target user and is used as the matched keyword information.
5. The method according to claim 1, wherein the obtaining of the information to be pushed of the target user comprises:
calculating to obtain the keyword information of each interest preference of the target user according to the history of the target user through a multi-dimensional user portrait interest model;
acquiring keyword information of each information in an information base to be pushed;
matching the keyword information of each interest preference of the target user with the keyword information of each information in the information base to be pushed, and selecting the information in the corresponding information base to be pushed with the highest matching degree as the information to be pushed.
6. The method according to claim 5, wherein the obtaining of the keyword information of each information in the information base to be pushed comprises
Acquiring information screened according to a preset screening rule and/or information uploaded by a target user;
acquiring and sequencing according to the information screened according to the preset screening rule and/or the updating time of the information uploaded by the target user;
and acquiring the keyword information of the first N pieces of information with latest updating time in the information screened according to the preset screening rule and/or the information uploaded by the target user.
7. The method of claim 5, wherein the obtaining of the keyword information of each interest preference of the target user through the multi-dimensional user representation interest model and the calculation according to the history of the target user comprises:
acquiring a historical browsing record and/or a historical watching record of the target user;
and inputting the historical browsing record and/or the historical watching record of the target user into a pre-trained multi-dimensional user image interest model, and calculating to obtain the keyword information of each interest preference of the target user.
8. The method according to claim 5, wherein the matching of the keyword information of each interest preference of the target user with the keyword information of each information in the information base to be pushed and the selection of the information in the information base to be pushed with the highest matching degree as the information to be pushed comprises:
inputting the keyword information of each interest preference of the target user and the keyword information of each information in the information base to be pushed into a pre-trained algorithm prediction model to obtain a matching degree score of the keyword information of each interest preference and the keyword information of each information in the information base to be pushed;
and selecting the information in the information base to be pushed with the highest matching degree as the information to be pushed.
9. A pushed document generation apparatus, comprising:
the information to be pushed acquisition module is used for acquiring information to be pushed of a target user;
the keyword information determining module is used for determining the keyword information of the information to be pushed and the keyword information of the interest preference of the target user;
the keyword information matching module is used for matching the keyword information of the information to be pushed with the keyword information of each interest preference of the target user to obtain the keyword information which is matched with the keyword information of the information to be pushed in the keyword information of each interest preference of the target user;
and the to-be-pushed document generation module is used for generating a to-be-pushed document according to the matched keyword information and pushing the to-be-pushed document to the target user.
10. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of claims 1 to 8 when executing a program stored in the memory.
11. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of the claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110571716.7A CN113177160B (en) | 2021-05-25 | 2021-05-25 | Push text generation method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110571716.7A CN113177160B (en) | 2021-05-25 | 2021-05-25 | Push text generation method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113177160A true CN113177160A (en) | 2021-07-27 |
| CN113177160B CN113177160B (en) | 2024-04-23 |
Family
ID=76928210
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110571716.7A Active CN113177160B (en) | 2021-05-25 | 2021-05-25 | Push text generation method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113177160B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643070A (en) * | 2021-08-20 | 2021-11-12 | 林秀珍 | Intelligent information pushing method and system based on big data |
| CN113744066A (en) * | 2021-09-01 | 2021-12-03 | 杭州隆埠科技有限公司 | Information pushing method and device |
| CN114722188A (en) * | 2022-06-09 | 2022-07-08 | 北京鑫宇创世科技有限公司 | Advertisement generation method, device and equipment based on operation data and storage medium |
Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1353485A2 (en) * | 2002-03-28 | 2003-10-15 | Nokia Corporation | User interface for pushing information in a short range radio mobile terminal |
| US20120036144A1 (en) * | 2009-02-27 | 2012-02-09 | Kabushiki Kaisha Toshiba | Information and recommendation device, method, and program |
| CN106227786A (en) * | 2016-07-19 | 2016-12-14 | 百度在线网络技术（北京）有限公司 | Method and apparatus for pushed information |
| CN106407425A (en) * | 2016-09-27 | 2017-02-15 | 北京百度网讯科技有限公司 | A method and a device for information push based on artificial intelligence |
| CN107291755A (en) * | 2016-04-01 | 2017-10-24 | 中国移动通信有限公司研究院 | A kind of terminal method for pushing and device |
| CN107943775A (en) * | 2017-11-24 | 2018-04-20 | 泰康保险集团股份有限公司 | Method, apparatus, storage medium and the electronic equipment of message push |
| CN108306814A (en) * | 2017-08-11 | 2018-07-20 | 腾讯科技（深圳）有限公司 | Information-pushing method, device, terminal based on instant messaging and storage medium |
| CN108563753A (en) * | 2018-04-16 | 2018-09-21 | 深圳壹账通智能科技有限公司 | Message pushes generation method, device and the computer readable storage medium of official documents and correspondence |
| CN108900612A (en) * | 2018-06-29 | 2018-11-27 | 百度在线网络技术（北京）有限公司 | Method and apparatus for pushed information |
| KR101958936B1 (en) * | 2018-01-23 | 2019-03-19 | 주식회사 이노피아테크 | Method and system for constructing content of interest in a tv channel |
| CN110209941A (en) * | 2019-06-03 | 2019-09-06 | 北京卡路里信息技术有限公司 | Method, method for pushing, device, medium and the server of maintenance push content pool |
| CN110365497A (en) * | 2019-05-29 | 2019-10-22 | 平安科技（深圳）有限公司 | Information push method, device, electronic equipment and storage medium |
| KR102098537B1 (en) * | 2019-08-05 | 2020-04-07 | 주식회사 네오인터랙티브 | Advertisement service system capable of providing advertisement material template for auto multilink based on analyzing bigdata and advertisement method thereof |
| CN111198986A (en) * | 2019-12-17 | 2020-05-26 | 中国平安人寿保险股份有限公司 | Information sending method and device, electronic equipment and storage medium |
| US20200234217A1 (en) * | 2019-01-22 | 2020-07-23 | International Business Machines Corporation | Operations augmented enterprise collaborative recommender engine |
| CN111768234A (en) * | 2020-06-28 | 2020-10-13 | 百度在线网络技术（北京）有限公司 | Method and device for generating recommended case for user, electronic device and medium |
| CN111797353A (en) * | 2020-07-03 | 2020-10-20 | 北京字节跳动网络技术有限公司 | Information pushing method and device and electronic equipment |
| CN111797315A (en) * | 2020-06-29 | 2020-10-20 | 深圳市锦囊互动技术有限公司 | Message pushing method, device, server and medium |
| CN112182378A (en) * | 2020-09-28 | 2021-01-05 | 厦门美柚股份有限公司 | Message pushing method, device, terminal and medium |
| CN112182197A (en) * | 2020-11-09 | 2021-01-05 | 北京明略软件系统有限公司 | Method, device and equipment for recommending dialect and computer readable medium |
| CN112202663A (en) * | 2020-09-28 | 2021-01-08 | 厦门美柚股份有限公司 | Message pushing method, device, terminal and medium |
-
2021
- 2021-05-25 CN CN202110571716.7A patent/CN113177160B/en active Active
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1353485A2 (en) * | 2002-03-28 | 2003-10-15 | Nokia Corporation | User interface for pushing information in a short range radio mobile terminal |
| US20120036144A1 (en) * | 2009-02-27 | 2012-02-09 | Kabushiki Kaisha Toshiba | Information and recommendation device, method, and program |
| CN107291755A (en) * | 2016-04-01 | 2017-10-24 | 中国移动通信有限公司研究院 | A kind of terminal method for pushing and device |
| CN106227786A (en) * | 2016-07-19 | 2016-12-14 | 百度在线网络技术（北京）有限公司 | Method and apparatus for pushed information |
| CN106407425A (en) * | 2016-09-27 | 2017-02-15 | 北京百度网讯科技有限公司 | A method and a device for information push based on artificial intelligence |
| CN108306814A (en) * | 2017-08-11 | 2018-07-20 | 腾讯科技（深圳）有限公司 | Information-pushing method, device, terminal based on instant messaging and storage medium |
| CN107943775A (en) * | 2017-11-24 | 2018-04-20 | 泰康保险集团股份有限公司 | Method, apparatus, storage medium and the electronic equipment of message push |
| KR101958936B1 (en) * | 2018-01-23 | 2019-03-19 | 주식회사 이노피아테크 | Method and system for constructing content of interest in a tv channel |
| CN108563753A (en) * | 2018-04-16 | 2018-09-21 | 深圳壹账通智能科技有限公司 | Message pushes generation method, device and the computer readable storage medium of official documents and correspondence |
| CN108900612A (en) * | 2018-06-29 | 2018-11-27 | 百度在线网络技术（北京）有限公司 | Method and apparatus for pushed information |
| US20200234217A1 (en) * | 2019-01-22 | 2020-07-23 | International Business Machines Corporation | Operations augmented enterprise collaborative recommender engine |
| CN110365497A (en) * | 2019-05-29 | 2019-10-22 | 平安科技（深圳）有限公司 | Information push method, device, electronic equipment and storage medium |
| CN110209941A (en) * | 2019-06-03 | 2019-09-06 | 北京卡路里信息技术有限公司 | Method, method for pushing, device, medium and the server of maintenance push content pool |
| KR102098537B1 (en) * | 2019-08-05 | 2020-04-07 | 주식회사 네오인터랙티브 | Advertisement service system capable of providing advertisement material template for auto multilink based on analyzing bigdata and advertisement method thereof |
| CN111198986A (en) * | 2019-12-17 | 2020-05-26 | 中国平安人寿保险股份有限公司 | Information sending method and device, electronic equipment and storage medium |
| CN111768234A (en) * | 2020-06-28 | 2020-10-13 | 百度在线网络技术（北京）有限公司 | Method and device for generating recommended case for user, electronic device and medium |
| CN111797315A (en) * | 2020-06-29 | 2020-10-20 | 深圳市锦囊互动技术有限公司 | Message pushing method, device, server and medium |
| CN111797353A (en) * | 2020-07-03 | 2020-10-20 | 北京字节跳动网络技术有限公司 | Information pushing method and device and electronic equipment |
| CN112182378A (en) * | 2020-09-28 | 2021-01-05 | 厦门美柚股份有限公司 | Message pushing method, device, terminal and medium |
| CN112202663A (en) * | 2020-09-28 | 2021-01-08 | 厦门美柚股份有限公司 | Message pushing method, device, terminal and medium |
| CN112182197A (en) * | 2020-11-09 | 2021-01-05 | 北京明略软件系统有限公司 | Method, device and equipment for recommending dialect and computer readable medium |
Non-Patent Citations (2)
| Title |
|---|
| 沈军彩;: "用户行为数据分析下的信息推送系统的设计", 现代电子技术, no. 17, 1 September 2017 (2017-09-01), pages 166 - 169 * |
| 潘红艳, 林鸿飞, 赵晶: "基于Ontology的个性化推送系统", 计算机工程与应用, no. 20, 1 August 2006 (2006-08-01), pages 179 - 183 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643070A (en) * | 2021-08-20 | 2021-11-12 | 林秀珍 | Intelligent information pushing method and system based on big data |
| CN113744066A (en) * | 2021-09-01 | 2021-12-03 | 杭州隆埠科技有限公司 | Information pushing method and device |
| CN113744066B (en) * | 2021-09-01 | 2024-04-02 | 杭州隆埠科技有限公司 | Information pushing method and device |
| CN114722188A (en) * | 2022-06-09 | 2022-07-08 | 北京鑫宇创世科技有限公司 | Advertisement generation method, device and equipment based on operation data and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113177160B (en) | 2024-04-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113177160B (en) | Push text generation method and device, electronic equipment and storage medium | |
| US10795939B2 (en) | Query method and apparatus | |
| CN110321422B (en) | Method for training model on line, pushing method, device and equipment | |
| CN106326391B (en) | Multimedia resource recommendation method and device | |
| CN109388760B (en) | Recommendation label obtaining method, media content recommendation method, device and storage medium | |
| CN109753601B (en) | Method and device for determining click rate of recommended information and electronic equipment | |
| CN112868004A (en) | Resource recommendation method and device, electronic equipment and storage medium | |
| CN110290199B (en) | Content pushing method, device and equipment | |
| US20190163828A1 (en) | Method and apparatus for outputting information | |
| US20180060788A1 (en) | System and method for attribute matching | |
| CN112330398A (en) | Object processing method and device, electronic equipment and storage medium | |
| CN112995765B (en) | Network resource display method and device | |
| CN111291217A (en) | Content recommendation method and device, electronic equipment and computer readable medium | |
| CN110971973A (en) | Video pushing method and device and electronic equipment | |
| CN110674330B (en) | Expression management method and device, electronic equipment and storage medium | |
| CN110275986B (en) | Video recommendation method based on collaborative filtering, server and computer storage medium | |
| CN110717109B (en) | Method, device, electronic equipment and storage medium for recommending data | |
| CN113536138A (en) | Network resource recommendation method and device, electronic equipment and readable storage medium | |
| CN116610853A (en) | Search recommendation method, search recommendation system, computer device, and storage medium | |
| CN114020799A (en) | Data acquisition method, data search method, data acquisition system, data search system, electronic device and storage medium | |
| CN116226523B (en) | Knowledge training method and system based on big data | |
| CN112818190A (en) | Content sharing method and device, electronic equipment and storage medium | |
| CN112115300A (en) | Text processing method and device, electronic equipment and readable storage medium | |
| CN108052503B (en) | Confidence coefficient calculation method and device | |
| CN111050194A (en) | Video sequence processing method, video sequence processing device, electronic equipment and computer readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |