CN110968777B - Information recommendation method, storage medium, electronic device and system - Google Patents
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Abstract
The invention discloses an information recommendation method, a storage medium, electronic equipment and a system, which relate to the technical field of communication, wherein the method comprises the steps of obtaining related information of a detail page, wherein the related information comprises recommendation interface information, the text content of the detail page, the content source of the detail page and a content author of the detail page; judging whether the recommendation interface is configured with advertisements or not according to the recommendation interface information; if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement; if the recommendation interface is not configured with advertisements, judging whether the text word number of the detail page is smaller than a first preset threshold value according to the text content of the detail page; when the text word number of the detail page is smaller than a first preset threshold value, the recommendation interface is not displayed; and when the number of words of the text of the detail page is greater than or equal to a first preset threshold value, randomly obtaining a preset recommendation strategy, screening recommendation contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommendation strategy, and recommending in a recommendation interface.
Description
Technical Field
The invention relates to the technical field of communication, in particular to an information recommendation method, a storage medium, electronic equipment and a system.
Background
With the development of networks, forum communities have emerged. A group of users with similar interests are aggregated in the forum community, discussing various recently trending topics in various panels. In the forum, the most basic target of the user is to read content acquisition information. Therefore, in order to provide more contents for the user, when the user reads one content, the content related to the theme is automatically recommended for the user, the user can conveniently obtain related information, and the viscosity and the click rate of the website are increased.
The existing content recommendation method is a recommendation method based on user browsing behaviors, and the method assumes that users browsing the same content have the same interest, so that the browsing behaviors of the users in a forum are analyzed, keywords of the browsed content are extracted, then the keywords, synonyms of the keywords and the like are used for obtaining a recommendation result, and the recommendation result is recommended to the users. However, in a live forum such as a fish bar, many users publish posts/dynamic states too spoken, so that it is difficult to extract keywords and associate the posts/dynamic states with related topics, and a plurality of posts/dynamic states are difficult to associate with each other through keywords even if the topics are related or similar. Therefore, based on the state of the live forum, a new recommendation method for non-associated keywords is urgently needed.
Disclosure of Invention
In view of the defects in the prior art, an object of the present invention is to provide an information recommendation method, a storage medium, an electronic device and a system, which can display dynamic/post with high relevance to a detail page currently browsed by a user on a recommendation interface.
In order to achieve the above object, in a first aspect, an embodiment of the present invention provides an information recommendation method, including obtaining relevant information of a detail page, where the relevant information includes recommendation interface information, content of a text of the detail page, a content source of the detail page, and a content author of the detail page; judging whether the recommendation interface is configured with advertisements or not according to the recommendation interface information; if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement; if the advertisement is not configured on the recommendation interface, judging whether the text word number of the detail page is smaller than a first preset threshold value according to the text content of the detail page; when the text word number of the detail page is smaller than a first preset threshold value, the recommendation interface is not displayed; and when the text word number of the detail page is greater than or equal to a first preset threshold value, randomly obtaining a preset recommendation strategy, screening recommendation contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommendation strategy, and recommending in the recommendation interface.
Optionally, when the number of text words of the detail page is greater than or equal to a first preset threshold, randomly obtaining a preset recommendation policy, screening recommendation contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommendation policy, and recommending in the recommendation interface specifically includes: when the randomly obtained preset recommendation strategy is a small compilation selection, selecting a first preset number of pre-selected recommendation data in a recommendation pool; judging the word number of the texts of all the preselected recommendation data one by one, and deleting the preselected recommendation data of which the word number is smaller than a second preset threshold value; when the number of the remaining pre-selected recommendation data is smaller than a third preset threshold value, the recommendation interface is not displayed; and when the number of the remaining pre-selected recommended data is larger than or equal to a third preset threshold, randomly selecting data with the number of the third preset threshold from the remaining pre-selected recommended data and displaying the data on the recommendation interface.
Optionally, when the number of text words of the detail page is greater than or equal to a first preset threshold, randomly obtaining a preset recommendation policy, screening recommendation content according to the content source of the detail page and/or the content author of the detail page according to the preset recommendation policy, and recommending on the recommendation interface further includes: when the randomly acquired preset recommendation strategy is source selection, judging the number of all posts issued at the source of the detail page; when the number of all posts is smaller than a fourth preset threshold value, screening according to the recommendation strategy selected by the small compilation; when the number of all posts is larger than or equal to a fourth preset threshold value, all posts are used as preselected recommended posts, and the posts with the word number smaller than the second preset threshold value in all the preselected recommended posts are deleted; when the number of the remaining preselected recommendation posts is smaller than a third preset threshold value, screening according to the recommendation strategy selected by the small catalog; and when the number of the remaining preselected recommended posts is larger than or equal to a third preset threshold value, randomly selecting posts with the number of the third preset threshold value from the remaining preselected recommended posts to display on the recommendation interface.
Optionally, when the number of text words of the detail page is greater than or equal to a first preset threshold, randomly obtaining a preset recommendation policy, screening recommendation content according to the content source of the detail page and/or the content author of the detail page according to the preset recommendation policy, and recommending on the recommendation interface further includes: when the randomly acquired preset recommendation strategy is the author selection, judging the number of fans of the author of the detail page; when the number of the fans is smaller than a fifth preset threshold value, screening according to a recommended strategy selected by the source; when the number of the fans is larger than or equal to a fifth preset threshold value, judging all dynamic numbers issued by the author of the detail page; when all the dynamic quantities are smaller than a fourth preset threshold value, screening according to the recommended strategy selected by the source; when the number of all the dynamic states is larger than or equal to a fourth preset threshold value, taking all the dynamic states as pre-selection recommended dynamic states, and deleting the dynamic states of which the word number is smaller than the second preset threshold value in all the pre-selection recommended dynamic states; when the remaining pre-selected recommended dynamic quantity is smaller than a third preset threshold value, screening according to the recommended strategy selected by the source; and when the number of the remaining pre-selected recommended dynamic states is larger than or equal to a third preset threshold value, randomly selecting a dynamic state with the number of a fourth preset threshold value from the remaining pre-selected recommended dynamic states to display on the recommendation interface.
Optionally, the first preset threshold, the second preset threshold, the third preset threshold, the fourth preset threshold, the fifth preset threshold, and the first preset number are default settings of a system or autonomous personalized settings of a user.
Optionally, the user autonomously sets any one or more of the preset recommendation strategies including the small compilation selection, the source selection and the author selection.
The optional information recommendation method further comprises the following steps: and when the text word number of the detail page is greater than or equal to a first preset threshold, if the user autonomously sets a preset recommendation strategy which does not contain any one of small editing selection, source selection or author selection, the recommendation interface is not displayed.
In a second aspect, an embodiment of the present invention further provides a storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the method in the embodiment of the first aspect.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a memory and a processor, where the memory stores a computer program running on the processor, and the processor executes the computer program to implement the method in the first aspect.
In a second aspect, an embodiment of the present invention provides an information recommendation interface display system, which includes: the acquisition module is used for acquiring related information of the detail page, wherein the related information comprises recommendation interface information, detail page text content, a detail page content source and a detail page content author; the judging module is used for judging whether the recommending interface is configured with the advertisement or not according to the recommending interface information acquired by the acquiring module; the control module is used for displaying the advertisement on the recommendation interface if the judgment module judges that the advertisement is configured on the recommendation interface; the judging module is used for judging whether the text word number of the detail page is smaller than a first preset threshold value according to the text content of the detail page acquired by the acquiring module if the judging module judges that the recommending interface is not configured with the advertisement; the control module is used for not displaying the recommendation interface when the judging module judges that the text word number of the detail page is smaller than a first preset threshold value; and the recommending module is used for randomly acquiring a preset recommending strategy when the judging module judges that the text word number of the detail page is greater than or equal to a first preset threshold value, screening recommended contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommending strategy, and recommending in the recommending interface.
Optionally, the recommending module specifically includes: the selecting unit is used for selecting a first preset number of pre-selected recommendation data from the recommendation pool when the randomly acquired preset recommendation strategy is a small compilation selection; the processing unit is used for judging the word number of the texts of all the preselected recommended data selected by the selecting unit one by one and deleting the preselected recommended data of which the word number is smaller than a second preset threshold value; the processing unit is used for not displaying the recommendation interface when the number of the remaining pre-selected recommendation data is smaller than a third preset threshold; and the selecting unit randomly selects data with the quantity of a third preset threshold value from the remaining pre-selected recommended data to be displayed on the recommending interface when the quantity of the remaining pre-selected recommended data is greater than or equal to the third preset threshold value.
Optionally, the recommending module further includes: the judging unit is used for judging the number of all posts issued from the source of the detail page when the randomly acquired preset recommendation strategy is source selection; the processing unit is used for screening according to the recommendation strategy of the small compilation selection when the number of all posts is smaller than a fourth preset threshold; when the number of all posts is larger than or equal to a fourth preset threshold value, all posts are used as preselected recommended posts, and the posts with the word number smaller than the second preset threshold value in all the preselected recommended posts are deleted; the processing unit is used for screening according to the selected recommendation strategy of the small compilation when the number of the remaining preselected recommendation posts is smaller than a third preset threshold value; and when the number of the remaining preselected recommended posts is greater than or equal to a third preset threshold value, the selecting unit randomly selects posts with the number of the third preset threshold value from the remaining preselected recommended posts and displays the posts on the recommendation interface.
Optionally, the recommending module further includes: the judging unit is used for judging the number of the fans of the author of the detail page when the randomly acquired preset recommendation strategy is the choice of the author; the processing unit is used for screening according to the recommended strategy selected by the source when the number of the fans is smaller than a fifth preset threshold value; the judging unit is used for judging all dynamic quantities issued by the author of the detail page when the number of the fans is greater than or equal to a fifth preset threshold; the processing unit is used for screening according to the recommended strategy selected by the source when all the dynamic quantities are smaller than a fourth preset threshold value; when the number of all the dynamic states is larger than or equal to a fourth preset threshold value, taking all the dynamic states as pre-selection recommended dynamic states, and deleting the dynamic states of which the word number is smaller than the second preset threshold value in all the pre-selection recommended dynamic states; the processing unit is used for screening according to the recommendation strategy selected by the source when the residual preselected recommendation dynamic quantity is smaller than a third preset threshold value; and when the number of the remaining pre-selected recommended dynamics is greater than or equal to a third preset threshold, the selecting unit randomly selects the dynamics with the number of a fourth preset threshold from the remaining pre-selected recommended dynamics to be displayed on the recommended interface.
Optionally, the information recommendation further includes: the setting module is used for setting a first preset threshold, a second preset threshold, a third preset threshold, a fourth preset threshold, a fifth preset threshold and a first preset number.
Optionally, the information recommendation further includes: the setting module is used for enabling a user to autonomously set any one or more of small compilation selection, source selection and author selection in the preset recommendation strategy.
Optionally, the information recommendation further includes: and when the text word number of the detail page is greater than or equal to a first preset threshold value, if the user autonomously sets a preset recommendation strategy which does not contain any one of small compilation selection, source selection or author selection, the recommendation interface is not displayed.
Compared with the prior art, the invention has the advantages that:
(1) the invention relates to an information recommendation method, a storage medium, an electronic device and an information recommendation system.
(2) The recommendation interface in the information recommendation method, the storage medium, the electronic device and the system displays the dynamic/post with high relevance to the detail page currently browsed by the user.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings corresponding to the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flowchart of an information recommendation method according to an embodiment of the present invention;
FIG. 2 is a flowchart of a second information recommendation method according to an embodiment of the present invention;
FIG. 3 is a flowchart of a third information recommendation method according to an embodiment of the present invention;
FIG. 4 is a flowchart of a fourth information recommendation method according to an embodiment of the present invention;
FIG. 5 is a flowchart of a fifth information recommendation method according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of six information recommendation systems according to embodiments of the present invention.
Detailed Description
Embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
Referring to fig. 1, embodiments of the present invention provide an information recommendation method, a storage medium, an electronic device, and a system, which are capable of displaying a dynamic/post with a high degree of correlation with a detail page currently browsed by a user on a recommendation interface through a preset recommendation policy.
Example one
An embodiment of the present invention provides an information recommendation method, as shown in fig. 1, which includes:
s1000, acquiring related information of the detail page, wherein the related information comprises recommendation interface information, the text content of the detail page, the content source of the detail page and the content author of the detail page;
s2000, judging whether the recommendation interface is configured with the advertisement or not according to the recommendation interface information;
s3000, if the advertisement is configured on the recommendation interface, displaying the advertisement on the recommendation interface;
s4000, if the advertisement is not configured on the recommendation interface, judging whether the number of words in the text of the detail page is smaller than a first preset threshold value according to the text of the detail page;
s5000, when the text word number of the detail page is smaller than a first preset threshold value, the recommendation interface is not displayed;
and S6000, when the number of words of the text of the detail page is larger than or equal to a first preset threshold value, randomly acquiring a preset recommendation strategy, screening recommendation contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommendation strategy, and recommending in a recommendation interface.
Specifically, the detail page in this embodiment is a page in which a user includes the text content of a dynamic/post issued by an online friend in a live broadcast client, for example, a forum, a post and other online friend communication boards, the lower end of the page includes an online friend comment and a recommendation interface, the number of recommendation slots of the recommendation interface is limited, the recommendation interface is used for placing an advertisement or recommendation information, and the online friend comment is displayed when the recommendation interface is not displayed. The server acquires the related information of the detail page, wherein the related information comprises recommendation interface information, the text content of the detail page, the content source of the detail page and the content author of the detail page. And the server judges whether the recommendation interface is configured with the advertisement or not according to the recommendation interface information in the related information, and if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement instead of recommending the content related to the detail page for the user. The configuration of a description file is added in the detail page advertisement background, after a user fills in the description file, the configured advertisement will have a corresponding file description, and the advertisement area is clicked to open a corresponding webpage.
If the recommendation interface is not configured with advertisements, whether the text word number is smaller than a first preset threshold value is judged according to the text content of the detail page in the related information, if so, the recommendation interface is not displayed, and the online friend comments are displayed instead. And if the number of the text words of the detail page is greater than or equal to a first preset threshold value, randomly acquiring a preset recommendation strategy, and displaying a recommendation interface according to the relevant information and the preset recommendation strategy.
The recommendation interface displayed in the invention is based on the content of the detail page and displays the content related to the detail page, so that different users can possibly display the same content when entering the same detail page recommendation interface, but the preset recommendation strategy is randomly selected in the background, so that even if the same detail page is entered, different contents can be displayed every time the recommendation interface is entered.
Based on the same inventive concept, the present application provides the second embodiment, which is as follows.
Example two
An embodiment of the present invention provides an information recommendation method, as shown in fig. 2, which includes:
s6000, when the text word number of the detail page is larger than or equal to a first preset threshold value, randomly acquiring a preset recommendation strategy, screening recommendation contents according to the content source of the detail page and/or a content author of the detail page according to the preset recommendation strategy, and recommending in a recommendation interface;
s7000 if the user autonomously sets the preset recommendation strategy not to include any one of the small compilation selection, the source selection or the author selection, the recommendation interface is not displayed;
s8000 if the user sets the preset recommendation strategy independently, wherein the preset recommendation strategy comprises any one or more of compilation selection, source selection and author selection; the first preset threshold, the second preset threshold, the third preset threshold, the fourth preset threshold, the fifth preset threshold and the first preset number are system default settings or user-independent personalized settings.
Specifically, in this embodiment, the server acquires the relevant information of the detail page, where the relevant information includes recommendation interface information, content of the detail page, a content source of the detail page, and a content author of the detail page. And the server judges whether the recommendation interface is configured with the advertisement or not according to the recommendation interface information in the related information, and if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement instead of recommending the content related to the detail page for the user. If the recommendation interface is not configured with advertisements, whether the text word number is smaller than a first preset threshold value is judged according to the text content of the detail page in the related information, and if yes, the recommendation interface is not displayed. And if the number of the text words of the detail page is greater than or equal to a first preset threshold value, randomly acquiring a preset recommendation strategy, and displaying a recommendation interface according to the relevant information and the preset recommendation strategy.
The preset recommendation strategies comprise small editing selection, source selection and author selection, and a user can autonomously set whether the corresponding recommendation strategy is started or not. If the user sets that all the preset recommendation strategies are not started, namely the user does not need to recommend in the background, the recommendation interface is not displayed. And if the user sets any one or more of the starting small compilation selection, the source selection and the author selection, randomly selecting one of the recommendation strategies started by the user to select the recommendation content to be displayed on the recommendation interface. All the preset thresholds in the recommended content selection process can be set by default in the system, can also be set by the user independently, and can be the same or different.
Various modifications and specific examples in the foregoing method embodiments are also applicable to the system of the present embodiment, and the detailed description of the method is clear to those skilled in the art, so that the detailed description is omitted here for the sake of brevity.
Based on the same inventive concept, the present application provides the third embodiment.
EXAMPLE III
The embodiment of the invention provides an information recommendation method, as shown in fig. 3, in S6000, when the number of text words of a detail page is greater than or equal to a first preset threshold, a preset recommendation policy is randomly obtained, recommended contents are screened according to a content source of the detail page and/or a content author of the detail page according to the preset recommendation policy, and the recommendation in a recommendation interface specifically includes:
s6110 when the randomly acquired preset recommendation strategy is a small compilation selection, selecting a first preset amount of pre-selected recommendation data from a recommendation pool;
s6120 judging the word number of the text of all the preselected recommendation data one by one, and deleting the preselected recommendation data with the word number smaller than a second preset threshold;
s6130, when the number of the remaining pre-selected recommended data is smaller than a third preset threshold, the recommended interface is not displayed;
s6140 when the number of the remaining pre-selected recommended data is larger than or equal to a third preset threshold, randomly selecting data with the number of the third preset threshold from the remaining pre-selected recommended data and displaying the data on a recommendation interface.
Specifically, in this embodiment, the server acquires the relevant information of the detail page, where the relevant information includes recommendation interface information, content of the detail page, a content source of the detail page, and a content author of the detail page. And the server judges whether the recommendation interface is configured with the advertisement or not according to the recommendation interface information in the related information, and if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement instead of recommending the content related to the detail page for the user. If the recommendation interface is not configured with advertisements, whether the text word number is smaller than a first preset threshold value is judged according to the text content of the detail page in the related information, and if yes, the recommendation interface is not displayed. And if the number of the text words of the detail page is greater than or equal to a first preset threshold value, randomly acquiring a preset recommendation strategy, and displaying a recommendation interface according to the relevant information and the preset recommendation strategy.
When the randomly obtained preset recommendation strategy is a small compilation selection, a first preset number of pre-selected recommendation data are selected from a recommendation pool, the data in the recommendation pool are selected and collected by background staff in the working process, the data in the recommendation pool can be arranged according to arrangement strategies set by the background staff, such as staff collection time arrangement or recommended times arrangement, and then the data arranged in the front are selected as required. And judging the word number of the texts of all the selected preselected recommended data one by one, and deleting the preselected recommended data of which the word number is smaller than a second preset threshold value, wherein the data with too few text words contains too few contents, so that the user experience is influenced when the data are recommended. When the background staff selects the collected data, the background staff may only roughly browse the theme or title, so that the situation that the text of the data in the recommendation pool has fewer words occurs, and when the data with too few words is found in the selection process, the corresponding data can also be deleted in the recommendation pool, so that the workload of subsequent selection is reduced, and the recommendation pool is further selected. And after the preselected recommendation data are further deleted according to the text word number, judging the number of the remaining preselected recommendation data, and if the number of the remaining preselected recommendation data is smaller than a third preset threshold value, not displaying the recommendation interface. And when the number of the remaining pre-selected recommended data is larger than or equal to a third preset threshold, randomly selecting data with the number of the third preset threshold from the remaining pre-selected recommended data and displaying the data on a recommendation interface. And the third preset threshold is the number of the recommendation bits of the recommendation interface, and when the recommendation data finally screened out through the recommendation strategy is smaller than the number of the recommendation bits, the recommendation interface is not selected to be displayed for the consideration of the page attractiveness.
Various modifications and specific examples in the foregoing method embodiments are also applicable to the system of the present embodiment, and the detailed description of the method is clear to those skilled in the art, so that the detailed description is omitted here for the sake of brevity.
Based on the same inventive concept, the present application provides the fourth embodiment.
Example four
An embodiment of the present invention provides an information recommendation method, as shown in fig. 4, in S6000, when the number of text words in the detail page is greater than or equal to a first preset threshold, a preset recommendation policy is randomly obtained, recommended contents are screened according to a content source of the detail page and/or a content author of the detail page according to the preset recommendation policy, and recommendation is performed on a recommendation interface, where the method further includes:
s6210, when the randomly acquired preset recommendation strategy is source selection, judging the number of all posts at the source of the release detail page;
s6220, when the number of all posts is smaller than a fourth preset threshold value, screening according to a recommendation strategy selected by the small catalog;
s6230, when the number of all posts is larger than or equal to a fourth preset threshold value, all posts are used as preselected recommended posts, and the posts with the word number smaller than the second preset threshold value in all the preselected recommended posts are deleted;
s6240 when the number of the remaining preselected recommendation posts is less than a third preset threshold, screening according to the recommendation strategy selected by the small catalog;
s6250 when the number of the remaining preselected recommended posts is greater than or equal to a third preset threshold, randomly selecting posts with the number of the third preset threshold from the remaining preselected recommended posts and displaying the posts on the recommendation interface.
Specifically, in this embodiment, the server acquires the relevant information of the detail page, where the relevant information includes recommendation interface information, content of the detail page, a content source of the detail page, and a content author of the detail page. And the server judges whether the recommendation interface is configured with the advertisement or not according to the recommendation interface information in the related information, and if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement instead of recommending the content related to the detail page for the user. If the recommendation interface is not configured with advertisements, whether the text word number is smaller than a first preset threshold value is judged according to the text content of the detail page in the related information, and if yes, the recommendation interface is not displayed. And if the number of the text words of the detail page is greater than or equal to a first preset threshold value, randomly acquiring a preset recommendation strategy, and displaying a recommendation interface according to the relevant information and the preset recommendation strategy.
When the randomly acquired preset recommendation strategy is source selection, judging the number of all posts at the source of the release detail page. And when the number of all posts is less than a fourth preset threshold value, screening according to the recommendation strategy of the small cataloguing selection, and when the number of posts at the source is too small, screening valuable posts difficultly, so that the small cataloguing selection recommendation strategy is changed into the above-mentioned recommendation strategy for screening. And when the number of all posts at the source is larger than or equal to a fourth preset threshold value, all posts are used as the preselected recommended posts, and the posts with the word number smaller than the second preset threshold value in the preselected recommended posts are deleted. And after the posts at the source are screened according to the text word number, when the number of the remaining preselected recommended posts is less than a third preset threshold value, screening according to a small selected recommendation strategy. And when the number of the remaining preselected recommended posts is larger than or equal to a third preset threshold value, randomly selecting posts with the number of a fourth preset threshold value from the remaining preselected recommended posts and displaying the posts on a recommendation interface.
Various modifications and specific examples in the foregoing method embodiments are also applicable to the system of the present embodiment, and the detailed description of the method is clear to those skilled in the art, so that the detailed description is omitted here for the sake of brevity.
Based on the same inventive concept, the present application provides embodiment five.
EXAMPLE five
As shown in fig. 5, in S6000, when the number of text words in the detail page is greater than or equal to a first preset threshold, a preset recommendation policy is randomly acquired, recommended contents are screened according to a preset recommendation policy according to a source of content in the detail page and/or an author of the content in the detail page, and recommendation is performed on a recommendation interface, further including:
s6310, when the randomly acquired preset recommendation strategy is the choice of authors, judging the number of fans of the authors of the detail page;
s6320, when the number of the fans is smaller than a fifth preset threshold value, screening according to a recommended strategy selected by the source;
s6330, when the number of the fans is larger than or equal to a fifth preset threshold value, judging all dynamic numbers issued by the author of the detail page;
s6340, when all the dynamic quantities are smaller than a fourth preset threshold value, screening according to a recommended strategy selected by a source;
s6350, when the number of all the dynamics is larger than or equal to a fourth preset threshold value, all the dynamics are used as pre-selection recommendation dynamics, and the dynamics with the word number smaller than the second preset threshold value in all the pre-selection recommendation dynamics are deleted;
s6360, when the remaining pre-selected recommended dynamic quantity is smaller than a third preset threshold value, screening according to a recommended strategy selected by a source;
s6370, when the number of the remaining pre-selected recommended dynamics is greater than or equal to the third preset threshold, randomly selecting the dynamics with the number of the fourth preset threshold from the remaining pre-selected recommended dynamics to display on the recommendation interface.
Specifically, in this embodiment, the server acquires the relevant information of the detail page, where the relevant information includes recommendation interface information, content of the detail page, a content source of the detail page, and a content author of the detail page. And the server judges whether the recommendation interface is configured with the advertisement or not according to the recommendation interface information in the related information, and if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement instead of recommending the content related to the detail page for the user. If the recommendation interface is not configured with advertisements, whether the text word number is smaller than a first preset threshold value is judged according to the text content of the detail page in the related information, and if yes, the recommendation interface is not displayed. And if the number of the text words of the detail page is greater than or equal to a first preset threshold value, randomly acquiring a preset recommendation strategy, and displaying a recommendation interface according to the relevant information and the preset recommendation strategy.
When the randomly acquired preset recommendation strategy is author selection, the number of fans of the author of the detail page is judged, and when the number of fans is smaller than a fifth preset threshold value, screening is carried out according to the recommendation strategy of source selection, because when the number of fans of the author is small, the attention of the author is insufficient or the state published before is not attractive enough, and the recommended value is not high. And when the number of the fans is larger than or equal to a fifth preset threshold value, judging all dynamic numbers issued by the author of the detail page. When all the dynamic quantities are less than the fourth preset threshold value, screening is carried out according to the recommendation strategy of source selection, because if all the dynamic quantities issued by the authors are too small, the subsequent screening is difficult to pass, and valuable dynamic quantities are difficult to screen. And when all the dynamic numbers are greater than or equal to a fourth preset threshold value, all the dynamic numbers are used as pre-selection recommended dynamic numbers, and the dynamic numbers, smaller than the second preset threshold value, in the pre-selection recommended dynamic numbers are deleted. And after the pre-selection recommendation dynamic is screened according to the text word number, when the residual pre-selection recommendation dynamic number is smaller than a third preset threshold value, screening according to a recommendation strategy of source selection. And when the number of the remaining pre-selected recommended dynamic states is larger than or equal to a third preset threshold value, randomly selecting the dynamic states with the number of the third preset threshold value from the remaining pre-selected recommended dynamic states and displaying the dynamic states on a recommendation interface.
Although the recommendation strategies in the invention can be selected by an author in the sequence from source selection to small compilation selection, the preset recommendation strategies are not selected according to the sequence when being randomly selected, and the small compilation selection can be directly selected when the preset recommendation strategies are randomly selected. However, based on the above priorities, when selecting the open priority policy, the user must first open the small compilation selection before selecting to open the source selection or the author selection. When the user only starts editing selection and author selection, if the author selection is selected but no proper state is recommended and source selection cannot be adopted, the process directly jumps to small editing selection.
Various modifications and specific examples in the foregoing method embodiments are also applicable to the system of the present embodiment, and the detailed description of the method is clear to those skilled in the art, so that the detailed description is omitted here for the sake of brevity.
Based on the same inventive concept, the present application provides embodiment six.
EXAMPLE six
A sixth embodiment of the present invention provides an information recommendation interface display system 100, as shown in fig. 6, including:
the obtaining module 110 obtains relevant information of the detail page, where the relevant information includes recommendation interface information, content of the detail page, content source of the detail page, and content author of the detail page;
the judging module 120 judges whether the recommendation interface is configured with the advertisement according to the recommendation interface information acquired by the acquiring module 110;
the control module 130, if the judgment module 120 judges that the advertisement is configured on the recommendation interface, the recommendation interface displays the advertisement;
the judging module 120, if the judging module 120 judges that the recommendation interface is not configured with the advertisement, judging whether the number of words in the text of the detail page is smaller than a first preset threshold value according to the text of the detail page acquired by the acquiring module 110;
the control module 130 is used for recommending that the interface is not displayed when the judging module 120 judges that the text word number of the detail page is smaller than a first preset threshold;
and the recommending module 140, when the judging module 120 judges that the number of words in the text of the detail page is greater than or equal to the first preset threshold, randomly acquiring a preset recommending strategy, screening recommending contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommending strategy, and recommending in a recommending interface.
Various modifications and specific examples in the foregoing method embodiments are also applicable to the system of the present embodiment, and the detailed description of the method is clear to those skilled in the art, so that the detailed description is omitted here for the sake of brevity.
Based on the same inventive concept, the present application provides embodiment seven.
EXAMPLE seven
A seventh embodiment of the invention provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out all or part of the method steps of the first embodiment.
The present invention can implement all or part of the flow in the method of the first embodiment, and can also be implemented by using a computer program to instruct related hardware, where the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments can be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying said computer program code, a recording medium, a usb-disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a Random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, etc. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
Based on the same inventive concept, the present application provides embodiment eight.
Example eight
The eighth embodiment of the present invention further provides an electronic device, which includes a memory and a processor, where the memory stores a computer program running on the processor, and the processor executes the computer program to implement all or part of the method steps in the first embodiment.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware component, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like which is the control center for the computer device and which connects the various parts of the overall computer device using various interfaces and lines.
The memory may be used to store the computer programs and/or modules, and the processor may implement various functions of the computer device by running or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, video data, etc.) created according to the use of the cellular phone, etc. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Generally, compared with the conventional technology and the like, the information recommendation method, the storage medium, the electronic device and the system provided by the embodiment of the invention can display the dynamic/post with high relevance to the detail page currently browsed by the user on the recommendation interface through more characteristics and the preset recommendation strategy.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
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.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. An information recommendation method is applied to the field of live broadcast, and is characterized by comprising the following steps:
acquiring related information of the detail page, wherein the related information comprises recommendation interface information, the text content of the detail page, a content source of the detail page and a content author of the detail page;
judging whether the recommendation interface is configured with advertisements or not according to the recommendation interface information;
if the recommendation interface is configured with the advertisement, the recommendation interface displays the advertisement;
if the advertisement is not configured on the recommendation interface, judging whether the text word number of the detail page is smaller than a first preset threshold value according to the text content of the detail page;
when the text word number of the detail page is smaller than a first preset threshold value, the recommendation interface is not displayed;
and when the text word number of the detail page is greater than or equal to a first preset threshold value, randomly obtaining a preset recommendation strategy, screening recommendation contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommendation strategy, and recommending in the recommendation interface.
2. The information recommendation method according to claim 1, wherein when the number of text words in the detail page is greater than or equal to a first preset threshold, a preset recommendation policy is randomly obtained, recommended contents are screened according to the preset recommendation policy according to the source of the content in the detail page and/or an author of the content in the detail page, and the recommending in the recommendation interface specifically includes:
when the randomly obtained preset recommendation strategy is a small compilation selection, selecting a first preset number of pre-selected recommendation data in a recommendation pool;
judging the word number of the texts of all the preselected recommendation data one by one, and deleting the preselected recommendation data of which the word number is smaller than a second preset threshold value;
when the number of the remaining pre-selected recommendation data is smaller than a third preset threshold value, the recommendation interface is not displayed;
and when the number of the remaining pre-selected recommended data is larger than or equal to a third preset threshold, randomly selecting data with the number of the third preset threshold from the remaining pre-selected recommended data and displaying the data on the recommendation interface.
3. The information recommendation method of claim 2, wherein when the number of text words in the detail page is greater than or equal to a first preset threshold, randomly obtaining a preset recommendation policy, filtering recommended contents according to the preset recommendation policy according to the source of the content in the detail page and/or the author of the content in the detail page, and recommending in the recommendation interface further comprises:
when the randomly acquired preset recommendation strategy is source selection, judging the number of all posts issued at the source of the detail page;
when the number of all posts is smaller than a fourth preset threshold value, screening according to the recommendation strategy selected by the small compilation;
when the number of all posts is larger than or equal to a fourth preset threshold value, all posts are used as preselected recommended posts, and the posts with the word number smaller than the second preset threshold value in all the preselected recommended posts are deleted;
when the number of the remaining preselected recommendation posts is smaller than a third preset threshold value, screening according to the recommendation strategy selected by the small catalog;
and when the number of the remaining preselected recommended posts is larger than or equal to a third preset threshold value, randomly selecting posts with the number of the third preset threshold value from the remaining preselected recommended posts to display on the recommendation interface.
4. The information recommendation method of claim 3, wherein when the number of text words in the detail page is greater than or equal to a first preset threshold, randomly obtaining a preset recommendation strategy, filtering recommendation contents according to the preset recommendation strategy according to the source of the content in the detail page and/or an author of the content in the detail page, and recommending in the recommendation interface further comprises:
when the randomly acquired preset recommendation strategy is the author selection, judging the number of fans of the author of the detail page;
when the number of the fans is smaller than a fifth preset threshold value, screening according to a recommended strategy selected by the source;
when the number of the fans is larger than or equal to a fifth preset threshold value, judging all dynamic numbers issued by the author of the detail page;
when all the dynamic quantities are smaller than a fourth preset threshold value, screening according to the recommended strategy selected by the source;
when the number of all the dynamic states is larger than or equal to a fourth preset threshold value, taking all the dynamic states as pre-selection recommended dynamic states, and deleting the dynamic states of which the word number is smaller than the second preset threshold value in all the pre-selection recommended dynamic states;
when the remaining pre-selected recommendation dynamic quantity is smaller than a third preset threshold value, screening according to the recommendation strategy selected by the source;
and when the number of the remaining pre-selected recommended dynamic states is larger than or equal to a third preset threshold value, randomly selecting a dynamic state with the number of a fourth preset threshold value from the remaining pre-selected recommended dynamic states to display on the recommendation interface.
5. The information recommendation method of claim 4, wherein: the first preset threshold, the second preset threshold, the third preset threshold, the fourth preset threshold, the fifth preset threshold and the first preset number are system default settings or user-independent personalized settings.
6. The information recommendation method of claim 4, wherein: the user autonomously sets any one or more of the preset recommendation strategies including small compilation selection, source selection and author selection.
7. The information recommendation method of claim 6, wherein the information recommendation method further comprises:
and when the text word number of the detail page is larger than or equal to a first preset threshold, if the user autonomously sets a preset recommendation strategy which does not comprise any one of small editing selection, source selection or author selection, the recommendation interface is not displayed.
8. A storage medium having a computer program stored thereon, characterized in that: the computer program, when executed by a processor, implements the method of any one of claims 1 to 7.
9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program that runs on the processor, characterized in that: the processor, when executing the computer program, implements the method of any of claims 1 to 7.
10. An information recommendation system, comprising:
the acquisition module is used for acquiring related information of the detail page, wherein the related information comprises recommendation interface information, detail page text content, a detail page content source and a detail page content author;
the judging module is used for judging whether the recommending interface is configured with the advertisement or not according to the recommending interface information acquired by the acquiring module;
the control module is used for displaying the advertisement on the recommendation interface if the judgment module judges that the advertisement is configured on the recommendation interface;
the judging module is used for judging whether the text word number of the detail page is smaller than a first preset threshold value according to the text content of the detail page acquired by the acquiring module if the judging module judges that the recommending interface is not configured with the advertisement;
the control module is used for not displaying the recommendation interface when the judging module judges that the text word number of the detail page is smaller than a first preset threshold value;
and the recommending module is used for randomly acquiring a preset recommending strategy when the judging module judges that the text word number of the detail page is greater than or equal to a first preset threshold value, screening recommended contents according to the content source of the detail page and/or the content author of the detail page according to the preset recommending strategy, and recommending in the recommending interface.
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