Information interaction method and device and related product

Abstract

The embodiment of the invention provides an information interaction method and device and a related product. The information interaction method comprises the steps that a target page is displayed; recommendation data used for recommending multimedia resources are displayed in the target page; in response to an operation behavior aiming at the multimedia resource based on the recommendation data, determining a target behavior type corresponding to the operation behavior; based on the target behavior type, determining a target component in each interaction component of the target page, and determining first prompt information corresponding to the target component; the interaction component is used for interacting with the recommendation data; the first prompt information is displayed in the target page; the first prompt information is used for prompting interaction with the recommendation data based on the target component.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, and in particular, to an information interaction method, apparatus, and related products. Background Art

[0002] In related technologies, a user can publish recommendation data for multimedia resources, and recommend the multimedia resources to other users through the recommendation data. A user who browses the recommendation data can select an interested multimedia resource according to the recommendation data. For example, a book-recommending user can post a thread in a reading application to recommend an e-book through the thread. A thread-browsing user can browse the thread and select an interested e-book for reading under the recommendation of the thread. In the above scenarios, the views and feelings of the user on the multimedia resources recommended in the recommendation data can be used as one of the important reference information for the operation platform to evaluate and screen high-quality multimedia resources. Based on this, how to efficiently obtain the views and feelings of the user on the multimedia resources recommended in the recommendation data and improve the efficiency of determining high-quality multimedia resources is one of the problems to be solved. Summary of the Invention

[0003] Embodiments of the present disclosure provide an information interaction method, apparatus, and related products, which can display a prompt message to prompt the user to interact with the recommendation data, so as to obtain the views and feelings of the user on the multimedia resources recommended in the recommendation data and improve the efficiency of determining high-quality multimedia resources.

[0004] In a first aspect, embodiments of the present disclosure provide an information recommendation interaction method, including: Displaying a target page; the target page displays recommendation data for recommending multimedia resources; Responding to an operation behavior on the multimedia resource based on the recommendation data, and determining a target behavior type corresponding to the operation behavior; Based on the target behavior type, determining a target component among the various interaction components on the target page, and determining a first prompt message corresponding to the target component; the interaction components are used to interact with the recommendation data; Displaying the first prompt message on the target page; the first prompt message is used to prompt to interact with the recommendation data based on the target component.

[0005] In a second aspect, embodiments of the present disclosure provide an information interaction apparatus, including: A first display module, configured to display a target page; the target page displays recommendation data for recommending multimedia resources; A first determination module, configured to respond to an operation behavior on the multimedia resource based on the recommendation data, and determine a target behavior type corresponding to the operation behavior; A second determination module, configured to determine a target component from each interactive component of the target page based on the target behavior type, and determine first prompt information corresponding to the target component; the interactive component is used to interact with the recommended data; A second display module, configured to display the first prompt information on the target page; the first prompt information is used to prompt interaction based on the target component and the recommended data.

[0006] In a third aspect, an embodiment of the present disclosure provides an electronic device, including: a processor; and a memory configured to store computer-executable instructions, where the computer-executable instructions, when executed, cause the processor to implement the method described in the first aspect above.

[0007] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, where the computer-readable storage medium is used to store computer-executable instructions, and the computer-executable instructions, when executed by a processor, implement the method described in the first aspect above.

[0008] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, where the computer program product includes a computer program, and the computer program, when executed by a processor, implements the method described in the first aspect above.

[0009] In one or more embodiments of the present disclosure, first, a target page is displayed, and recommended data for recommending multimedia resources is displayed on the target page. Then, in response to an operation behavior for a multimedia resource based on the recommended data, a target behavior type corresponding to the operation behavior is determined. Then, based on the target behavior type, a target component is determined from each interactive component of the target page, and first prompt information corresponding to the target component is determined. The interactive component is used to interact with the recommended data. Finally, the first prompt information is displayed on the target page, and the first prompt information is used to prompt interaction based on the target component and the recommended data. It can be seen that through the embodiments of the present disclosure, in a scenario where multimedia resources are recommended through recommended data, when a user performs an operation behavior of a target behavior type on a multimedia resource, based on the target behavior type, a target component can be determined from the interactive components used to interact with the recommended data, and first prompt information corresponding to the target component can be determined, and the first prompt information is displayed, and the user is prompted to interact based on the target component and the recommended data, so as to obtain the views and feelings of the user on the multimedia resources recommended in the recommended data, and improve the efficiency of determining high-quality multimedia resources. Description of the Drawings

[0010] To more clearly illustrate the technical solutions in one or more embodiments of the present disclosure or related technologies, the following will briefly introduce the drawings required for the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments recorded in the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings; Figure 1 Schematic flowchart of an information interaction method provided by an embodiment of the present disclosure; Figure 2a Schematic diagram of a target page provided by an embodiment of the present disclosure; Figure 2b Schematic diagram of a target page provided by another embodiment of the present disclosure; Figure 2c Schematic diagram of a target page provided by yet another embodiment of the present disclosure; Figure 3 Schematic diagram of each interactive component of a target page provided by an embodiment of the present disclosure; Figure 4 Schematic diagram of a target page showing a first prompt message provided by an embodiment of the present disclosure; Figure 5 Schematic diagram of a target page showing a first prompt message provided by another embodiment of the present disclosure; Figure 6 Schematic diagram of a topic page provided by an embodiment of the present disclosure; Figure 7 Schematic diagram of the structure of an information interaction device provided by an embodiment of the present disclosure; Figure 8 Schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. Detailed implementation manners

[0011] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of the present disclosure, the following will clearly and completely describe the technical solutions in one or more embodiments of the present disclosure in conjunction with the drawings in one or more embodiments of the present disclosure. Obviously, the described embodiments are only some embodiments of the present disclosure, rather than all embodiments. Based on one or more embodiments of the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present disclosure.

[0012] It can be understood that before using the technical solutions disclosed in the embodiments of the present disclosure, the type, scope of use, usage scenarios, etc. of the information involved in the present disclosure should be informed to the relevant parties and the authorization of the relevant parties should be obtained through appropriate means in accordance with relevant laws and regulations.

[0013] For example, when a user's active request is received, a prompt message is sent to the user to clearly prompt the user that the operation requested by the user will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application program, server, or storage medium that performs the operations of the present disclosure's technical solution based on the prompt message.

[0014] As an optional but non-limiting implementation manner, the manner of sending a prompt message to the user in response to receiving the user's active request may be, for example, in the form of a pop-up window. The prompt message may be presented in text in the pop-up window. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0015] It can be understood that the above notification and user authorization process is merely illustrative and does not limit the implementation manner of the present disclosure. Other manners that comply with relevant laws and regulations can also be applied to the implementation manner of the present disclosure.

[0016] The embodiments of the present disclosure provide an information interaction method, apparatus, and related products, which can display a prompt message, prompt the user to interact with the recommended data through the prompt message, so as to obtain the user's views and feelings on the multimedia resources recommended in the recommended data, and improve the efficiency of determining high-quality multimedia resources. Among them, the information interaction method can be applied to a terminal device and implemented by the terminal device. The terminal device includes, but is not limited to, various types of user terminals such as laptop computers, tablet computers, desktop computers, set-top boxes, mobile devices (for example, mobile phones, portable music players, personal digital assistants, dedicated messaging devices, portable game devices), smart phones, smart speakers, smart watches, smart TVs, in-vehicle terminals, etc.

[0017] Figure 1 It is a schematic flowchart of the information interaction method provided by an embodiment of the present disclosure, as Figure 1 shown. The process includes: Step S102: Display a target page; the recommended data for recommending multimedia resources is displayed in the target page; Step S104: In response to an operation behavior for a multimedia resource based on the recommended data, determine the target behavior type corresponding to the operation behavior; Step S106: Based on the target behavior type, determine a target component among the various interaction components of the target page, and determine the first prompt message corresponding to the target component; the interaction components are used to interact with the recommended data; Step S108: Display the first prompt message in the target page; the first prompt message is used to prompt interaction with the recommended data based on the target component.

[0018] In one or more embodiments of the present disclosure, first, a target page is displayed, and recommendation data for recommending multimedia resources is displayed on the target page. Then, in response to an operation behavior on the multimedia resource based on the recommendation data, a target behavior type corresponding to the operation behavior is determined. Next, based on the target behavior type, a target component is determined among the various interactive components on the target page, and a first prompt message corresponding to the target component is determined. The interactive components are used to interact with the recommendation data. Finally, the first prompt message is displayed on the target page, and the first prompt message is used to prompt interaction with the recommendation data based on the target component. It can be seen that through the embodiments of the present disclosure, in the scenario of recommending multimedia resources through recommendation data, when the user performs an operation behavior of the target behavior type on the multimedia resource, the target component can be determined among the interactive components for interacting with the recommendation data based on the target behavior type, and the first prompt message corresponding to the target component can be determined and displayed. The user is prompted to interact with the recommendation data based on the target component through the first prompt message, so as to obtain the user's views and feelings on the multimedia resources recommended in the recommendation data, and improve the efficiency of determining high-quality multimedia resources.

[0019] In step S102 above, the terminal device displays a target page, and recommendation data for recommending multimedia resources is displayed on the target page. The target page can be located in a reading application or a video viewing application. The multimedia resources can be exemplified as e-books, video data, etc. Among them, the video data includes short plays, short videos, movies, TV series, etc. Correspondingly, the recommendation data can include any one of a book recommendation post, a drama recommendation post, a drama recommendation video, and a book recommendation video. In this embodiment, a book recommendation post and a drama recommendation video are taken as examples for illustration. The drama recommendation post and the book recommendation video will not be elaborated. Among them, the drama recommendation video can be a collection video of wonderful clips in the video data. The book recommendation video can be an introduction video introducing the content of the e-book.

[0020] Figure 2a This is a schematic diagram of the target page provided by an embodiment of the present disclosure. In this example, a book recommendation post is used as an example for illustration. The target page may include multiple book recommendation posts. Schematically, Figure 2a only the book recommendation posts of the e-book "Comedy Collection" and the e-book "I Want to Be a Schoolmaster" are shown. The user can also view other book recommendation posts on the target page by swiping the screen up and down. Taking the book recommendation post of the e-book "Comedy Collection" as an example, the book recommendation post includes the user information of the user who posted the book recommendation post, the recommendation information of the e-book "Comedy Collection": "This 9.9 high-score novel is extremely funny! I laughed from the first chapter to the last chapter.", the cover image of the e-book "Comedy Collection", and the entry card of the e-book "Comedy Collection". If the user triggers, for example, Figure 2aThe entry card of the e-book "Comedy Collection" shown can jump to the reading page of the e-book "Comedy Collection", where the user can read the e-book "Comedy Collection". Figure 2a As shown, the target page also displays interactive components corresponding to the book recommendation post, such as a like component and a comment component.

[0021] Figure 2b This is a schematic diagram of a target page provided by another embodiment of the present disclosure. In this example, the recommended data is a book recommendation post as an example. Figure 2a and Figure 2b The difference is that in Figure 2a The target page shown may display multiple book recommendation posts, and the user can select the book recommendation posts of interest to read by swiping up and down. Figure 2a The recommended information of the e-book "Comedy Collection" in the book recommendation post shown in Figure 2b , Figure 2b Only the recommended book posts triggered by the user are displayed, and other recommended book posts are not displayed. Figure 2b and Figure 2a The displayed contents are basically the same and will not be repeated here. Figure 2b As shown, the target page also displays interactive components corresponding to the book recommendation post, such as a like component and a comment component. Figure 2b In the example, the comment component is illustrated by a comment box.

[0022] Figure 2c FIG. 1 is a schematic diagram of a target page provided by another embodiment of the present disclosure. In this example, the recommended data is a recommended drama video. Figure 2c As shown in the figure, the recommended drama video of the short drama "I Want to Be a Top Student" is displayed on the target page. The target page also displays the user information of the user who posted the recommended drama video, the drama recommendation information "This drama tells the story of a security guard's growth journey from a counterattack to a college student" and the playback entrance of the recommended short drama "I Want to Be a Top Student" "Click here to watch the drama". If the user triggers the following Figure 2c The recommended short play playback entrance shown in FIG. 1 can jump to the corresponding video playback page, where the user can watch the recommended short play "I Want to Be a Top Student". Figure 2c As shown, the target page also displays interactive components corresponding to the recommended drama video, such as a like component and a comment component.

[0023] After the target page is displayed, in the above step S104, in response to the operation behavior on the multimedia resource based on the recommendation data, the target behavior type corresponding to the operation behavior is determined. The terminal device can detect the user's operation behavior on the multimedia resource recommended in the recommendation data, and determine the target behavior type corresponding to the operation behavior based on the detected operation behavior.

[0024] In one embodiment, determining the target behavior type corresponding to the operation behavior includes: If the operation behavior is used to browse multimedia resources and the browsing duration is less than the duration threshold, determine that the target behavior type is the first type of browsing behavior; If the operation behavior is used to browse multimedia resources and the browsing duration is not less than the duration threshold, determine that the target behavior type is the second type of browsing behavior; If the operation behavior is used to browse multimedia resources and comment information is published for the multimedia resources, determine that the target behavior type is the browsing and commenting behavior; If the operation behavior is used to collect multimedia resources, determine that the target behavior type is the collection behavior.

[0025] In this embodiment, the duration threshold can be a preset time length, and the duration threshold can be exemplified as 10 minutes. If the operation behavior is used to browse multimedia resources and the browsing duration is less than the preset duration threshold, then, it can be determined that the target behavior type corresponding to the operation behavior is the first type of browsing behavior. If the operation behavior is used to browse multimedia resources and the browsing duration is not less than the preset duration threshold, then, it can be determined that the target behavior type corresponding to the operation behavior is the second type of browsing behavior. The comment information can express the user's feelings and views on the multimedia resources, and the comment information can be exemplified as: "This book is so wonderful!" and "The action of the male protagonist practicing sword in the play is so handsome!". If the operation behavior is used to browse multimedia resources and comment information is published for the multimedia resources, then, it can be determined that the target behavior type is the browsing and commenting behavior. Collecting multimedia resources can be exemplified as adding an e-book to the personal bookshelf or adding a short drama to the drama-watching list. If the operation behavior is used to collect multimedia resources, then, it can be determined that the target behavior type is the collection behavior.

[0026] In another embodiment, the number of target behavior types corresponding to the operation behavior can be multiple. For example, the target behavior types corresponding to the operation behavior include the second type of browsing behavior and the browsing and commenting behavior, that is, the user browses multimedia resources and the browsing duration is not less than the duration threshold, and comment information is published for the multimedia resources. Another example is that the target behavior types corresponding to the operation behavior include the second type of browsing behavior, the browsing and commenting behavior, and the collection behavior, that is, the user browses multimedia resources and the browsing duration is not less than the duration threshold, comment information is published for the multimedia resources, and the multimedia resources are collected.

[0027] In one example, taking the multimedia resource as the e-book "Comedy Compendium" as an example, assume that the duration threshold is 10 minutes. User A's browsing duration of the e-book "Comedy Compendium" is 15 minutes. After browsing, User A posted a comment on the e-book, and the comment is: "This book is so funny!" After posting the comment, User A also added the e-book to the personal bookshelf and collected the e-book. In the above example, the target behavior types corresponding to User A's operation behaviors for the e-book "Comedy Compendium" include the second type of browsing behavior, browsing and commenting behavior, and collection behavior.

[0028] It can be seen that through this embodiment, the target behavior type corresponding to the operation behavior of the user for the multimedia resource can be determined according to the behavior characteristics of the operation behavior, making the determination result of the target behavior type more accurate and improving the determination accuracy.

[0029] After determining the target behavior type corresponding to the operation behavior, in step S106, based on the target behavior type, the target component is determined among the various interactive components on the target page. The various interactive components on the target page are used for the user to interact with the recommended data so that the user can post views and feelings on the recommended multimedia data. The interactive components on the target page include at least one of a like component, a comment component, a collection component, and a share component. Among them, the like component is used to like the recommended data, the comment component is used to comment on the recommended data, the collection component is used to collect the recommended data, and the share component is used to share the recommended data with other users.

[0030] In one embodiment, determining the target component among the various interactive components on the target page based on the target behavior type includes: Obtaining the mapping relationship between the created target behavior type and each interactive component, and determining the interactive component corresponding to the target behavior type in the mapping relationship as the candidate interactive component; Obtaining the trigger records of the same-type components for the candidate interactive components, and determining the target component among the various candidate interactive components according to the trigger records.

[0031] In this embodiment, when determining the target component among the various interactive components on the target page, the mapping relationship between the created target behavior type and each interactive component can be obtained first, and based on the determined target behavior type, the interactive component corresponding to the target behavior type in the mapping relationship is determined as the candidate interactive component.

[0032] In one example, Figure 3 is a schematic diagram of the various interactive components on the target page provided by an embodiment of the present disclosure. As Figure 3 shown, the book recommendation post on the target page is the above-mentioned Figure 2aFor each of the recommended book posts shown, the interactive components on the target page include: a like component, a comment component, a favorite component, and a share component. Each of the interactive components on the target page is located below each recommended book post.

[0033] In one example, in the mapping relationship created between the created target behavior types and the respective interactive components, the interactive components corresponding to the first type of browsing behavior include a like component and a favorite component; the interactive components corresponding to the second type of browsing behavior include a like component, a comment component, and a favorite component; the interactive components corresponding to the browse-comment type of behavior include a like component, a comment component, a favorite component, and a share component; the interactive components corresponding to the favorite type of behavior include a like component, a favorite component, and a share component. Based on the above mapping relationship, when the determined target behavior type is the first type of browsing behavior, it can be determined that the candidate interactive components include a like component and a favorite component; when the determined target behavior type is the second type of browsing behavior, it can be determined that the candidate interactive components include a like component, a comment component, and a favorite component; when the determined target behavior type is the browse-comment type of behavior, it can be determined that the candidate interactive components include a like component, a comment component, a favorite component, and a share component; when the determined target behavior type is the favorite type of behavior, it can be determined that the candidate interactive components include a like component, a favorite component, and a share component. When the number of target behavior types is multiple, all the interactive components corresponding to each target behavior type can be jointly used as candidate interactive components.

[0034] Then, for each candidate interactive component, obtain the trigger records of the user for the same-type components of the candidate interactive component. Among them, the same-type components can be components with the same function as the candidate interactive component on other pages, and the other pages refer to pages other than the target page in the application where the target page is located. The trigger records of the user for the same-type components can be, for example, the historical trigger times of the user for the same-type components. The trigger records of the user for the same-type components can represent the user's usage habits and inclination degrees for each type of interactive component. Then, based on the trigger records of the user for the same-type components of the candidate interactive component, determine the target component among the candidate interactive components. Among them, the target component can be the candidate interactive component corresponding to the same-type component with the highest historical trigger times, and the target component can also be the candidate interactive component corresponding to the same-type component with the highest historical trigger times and the candidate interactive component corresponding to the same-type component with the second highest historical trigger times. The user here refers to the user who has performed the operation behavior of the target behavior type in this embodiment.

[0035] Continuing with the above example, assume that the target behavior type is the second type of browsing behavior, and the candidate interaction components for the second type of browsing behavior include a like component, a comment component, and a favorite component. The like components, comment components, and favorite components of other pages with like functions, comment functions, and favorite functions are the same type of components as the candidate interaction components for the second type of browsing behavior. This other page is exemplified as all other pages in the application where the target page is located except the target page. Assume that the historical trigger times of the user in this embodiment for the like component in all other pages are obtained as 50 times, the historical trigger times of the user in this embodiment for the comment component in all other pages are obtained as 40 times, and the historical trigger times of the user in this embodiment for the favorite component in all other pages are obtained as 20 times. According to the historical trigger times of the like components, comment components, and favorite components of the same type of each candidate interaction component, the like component and the comment component can be determined as the target components.

[0036] In another embodiment, since the determined target behavior type can be multiple, for example, the target behavior types include the first type of browsing behavior, browsing comment behavior, and favorite behavior. Therefore, when determining the target components among the interaction components of the target page, all the interaction components corresponding to each target behavior type can be jointly used as candidate interaction components, and through the above process, the target components are determined among the selected interaction components.

[0037] In yet another embodiment, the target components can also be fixed interaction components, that is, regardless of the type of the target behavior type, the target components are the like component and the comment component.

[0038] It can be seen that through this embodiment, according to the mapping relationship between the created target behavior type and each interaction component, the interaction component corresponding to the target behavior type in the mapping relationship can be determined as the candidate interaction component, and according to the trigger records of the like components of the same type of the candidate interaction components, the target components are determined among the candidate interaction components, making the determination result of the target components more accurate and making the determined target components match the behavior mode of the user in this embodiment.

[0039] After determining the target components among the interaction components of the target page based on the target behavior type, step S106 above also determines the first prompt information corresponding to the target components. The first prompt information corresponding to the target components can be used to prompt the user to interact based on the target components and the recommended data. For example, if the target component is a like component, the first prompt information can be exemplified as: "It's not easy to recommend books, give it a like!" or "Come and give it a like~".

[0040] In one embodiment, determining the first prompt information corresponding to the target components includes: Obtaining at least one candidate prompt information configured for the target behavior type and the target components; Determine the first prompt message among each candidate prompt message according to the interaction record corresponding to the candidate prompt message; the interaction record is an interaction record based on the interaction between the candidate prompt message and the recommended data.

[0041] In this embodiment, corresponding prompt messages are configured for each behavior type and each interaction component, that is, a corresponding relationship among the behavior type, the interaction component, and the prompt message is created. When determining the first prompt message corresponding to the target component, at least one prompt message configured for the target behavior type and the target component can be first obtained as the candidate prompt message, and then, according to the interaction record corresponding to each candidate prompt message, the first prompt message corresponding to the target component is determined among the obtained candidate prompt messages. Among them, the interaction record corresponding to the candidate prompt message is the interaction record of all network users based on the candidate prompt message and the recommended data in this embodiment when the candidate prompt message was once published as the first prompt message corresponding to the recommended data in this embodiment, and the interaction record can be the number of interactions. The interaction record corresponding to the candidate prompt message can indicate the quality of the prompt effect achieved after the candidate prompt message is published as the first prompt message corresponding to the recommended data in this embodiment. If a certain candidate prompt message was historically published as the first prompt message corresponding to the recommended data in this embodiment and the corresponding number of interactions is high, it means that the candidate prompt message is a more popular prompt message among users. The first prompt message can be the candidate prompt message corresponding to the highest number of interactions with the recommended data in this embodiment among each candidate prompt message.

[0042] In one example, the target behavior type is the behavior of browsing comments. The target component corresponding to this behavior of browsing comments is, for example, a comment component. The candidate prompt information configured for this behavior of browsing comments and the comment component is: "Looking forward to your comments!", "Stay and chat with me.", "Has it saved you from the lack of books to read? Let me know in the comment section~". Assume that for the recommended data in this embodiment, these three candidate prompt information have all been published as the first prompt information to facilitate interaction with the recommended data in this embodiment. And during the process of historically publishing these three candidate prompt information, it is detected that the number of times the whole network users interact with the recommended data in this embodiment based on the candidate prompt information "Looking forward to your comments!" is 50 times; it is detected that the number of times the whole network users interact with the recommended data in this embodiment based on the candidate prompt information "Stay and chat with me." is 70 times; it is detected that the number of times the whole network users interact with the recommended data in this embodiment based on the candidate prompt information "Has it saved you from the lack of books to read? Let me know in the comment section~" is 200 times. Among the above candidate prompt information, the number of interaction times of the whole network users interacting with the recommended data in this embodiment based on the candidate prompt information "Has it saved you from the lack of books to read? Let me know in the comment section~" is the highest. Therefore, "Has it saved you from the lack of books to read? Let me know in the comment section~" can be determined as the first prompt information.

[0043] The above method is applicable to the situation where each candidate prompt information has been published as the first prompt information corresponding to the recommended data in this embodiment. If any candidate prompt information has not been published as the first prompt information corresponding to the recommended data in this embodiment, then there is no corresponding interaction record for this unpublished candidate prompt information. In this case, one information can be randomly selected from the candidate prompt information as the first prompt information corresponding to the recommended data in this embodiment.

[0044] It can be seen that through this embodiment, the first prompt information can be determined from each candidate prompt information according to the interaction record corresponding to at least one candidate prompt information configured for the target behavior type and the target component, making the determination result of the first prompt information more accurate, increasing the possibility of users interacting with the recommended data based on the target component, and improving the effect of user interaction.

[0045] In another embodiment, determining the first prompt information corresponding to the target component includes: If the operation behavior is used to browse multimedia resources and the browsing duration is not less than the duration threshold, then determine the first content browsed in the multimedia resources; Generate the first prompt information corresponding to the target component according to the first content; the target component includes a comment component for the recommended data; the first prompt information is used to prompt commenting on the recommended data.

[0046] In this embodiment, when determining the first prompt information corresponding to the target component, if the operation behavior is used to browse multimedia resources and the browsing duration is not less than the duration threshold, that is, the target behavior type of the operation behavior is the second type of browsing behavior, then the first content browsed by the user can be determined in the multimedia resources. Then, according to the first content, the first prompt information corresponding to the target component is generated, where the target component includes a comment component for recommended data, and the first prompt information is used to prompt the user to comment on the recommended data.

[0047] In an example, user Xiaob watched the content of the first to tenth episodes of the short drama "Comedy Compendium" recommended by the recommended data, and the browsing duration was 30 minutes, exceeding the duration threshold of 10 minutes. The target behavior type corresponding to user Xiaob's operation behavior is the second type of browsing behavior. Then, the content of the first to tenth episodes of the short drama "Comedy Compendium" watched by user Xiaob can be determined as the first content. Then, according to the content of the first to tenth episodes of the short drama "Comedy Compendium", the first prompt information corresponding to the comment component of the recommended data is generated, and the user is guided to comment on the recommended data through the first prompt information.

[0048] It can be seen that through this embodiment, when the operation behavior is used to browse multimedia resources and the browsing duration is not less than the duration threshold, the first content browsed in the multimedia resources can be determined, and according to the first content, the first prompt information corresponding to the target component is generated, making the generation result of the first prompt information more accurate, increasing the possibility of user interaction based on the target component and the recommended data, and improving the effect of user interaction.

[0049] In one embodiment, generating the first prompt information corresponding to the target component according to the first content includes: Determining the knowledge points included in the first content through the first generative model, and generating knowledge Q&A texts corresponding to the knowledge points; Generating the first prompt information according to the knowledge Q&A text through the first generative model.

[0050] In this embodiment, when generating the first prompt information corresponding to the target component according to the first content, the knowledge points included in the first content can be determined first through the first generative model, and then, the knowledge Q&A texts corresponding to the knowledge points are generated through the first generative model. Then, through the first generative model, according to the generated knowledge Q&A text above, the first prompt information is generated. For example, the knowledge Q&A text is used as the first prompt information, or the knowledge Q&A text is modified and adjusted in terms of words to obtain the first prompt information.

[0051] When the multimedia resource is an e - book, the first content is in text form. The first content can be the content of the e - book text that the user has read. The first generative model can include a large - language model (LLM) trained using AI (Artificial Intelligence) technology. By using the large - language model to understand the content of the first content in text form, the knowledge points included in the first content are determined, and knowledge - based Q&A texts corresponding to the knowledge points are generated, and then the first prompt information is generated. When the multimedia resource is a short drama, the first content is in video form. The first content can be the content of the short - drama episodes that the user has watched. The first generative model can include a large - language model trained using AI technology and a video - content understanding model trained using AI technology. By using the video - content understanding model to understand the content of the first content in video form, the knowledge points included in the first content are determined, and the large - language model is used to generate knowledge - based Q&A texts corresponding to the knowledge points, and then the first prompt information is generated.

[0052] Continuing with the above example, the first content is the content of the first to tenth episodes of the short drama "Comedy Compendium" watched by user Xiaob. First, through the video - content understanding model in the first generative model, content - understanding processing is performed on the content of the first to tenth episodes of the short drama "Comedy Compendium" to determine the various knowledge points included in the content of the first to tenth episodes of the short drama "Comedy Compendium", such as: the female protagonist goes to college, the female protagonist becomes a teacher. Taking the knowledge point "the female protagonist goes to college" as an example, through the large - language model in the first generative model, knowledge - based Q&A texts corresponding to the knowledge point "the female protagonist goes to college" are generated, such as: "Do you think the plot of the female protagonist going to college is wonderful?" and "What college did the female protagonist go to?". Taking the knowledge - based Q&A text "Do you think the plot of the female protagonist going to college is wonderful?" as an example, through the large - language model in the first generative model, the first prompt information is generated based on the knowledge - based Q&A text "Do you think the plot of the female protagonist going to college is wonderful?", such as: "Do you think the plot of the female protagonist going to college is wonderful? Let's chat about it".

[0053] It can be seen that through this embodiment, the knowledge points included in the first content can be determined through the first generative model, knowledge - based Q&A texts corresponding to the knowledge points are generated, and the first prompt information is generated based on the knowledge - based Q&A texts, making the determination result of the first prompt information more accurate, increasing the possibility of user interaction based on the target component and recommended data, and improving the effect of user interaction.

[0054] In another embodiment, determining the first prompt information corresponding to the target component includes: If the operation behavior is used to browse the multimedia resource and post a comment message about the multimedia resource, then obtain the posted comment message; Generate a first prompt message corresponding to the target component according to the comment information; the target component includes a comment component for recommended data; the first prompt message includes the comment information to be commented on corresponding to the comment component.

[0055] In this embodiment, when determining the first prompt message corresponding to the target component, if the user's operation behavior is used to browse the multimedia resource and a comment message is published for the multimedia resource, that is, the target behavior type corresponding to the user's operation behavior is a browse-comment type behavior, then the comment information published by the user for the multimedia resource can be obtained, and according to this comment information, a first prompt message corresponding to the target component is generated. Among them, the target component includes a comment component for recommended data, and the first prompt message includes the comment information to be commented on corresponding to the comment component. The first prompt message can be displayed as the comment information to be commented on in the comment component. If the user wants to publish a comment message, he only needs to trigger the comment component to publish the comment message with one key. The comment message published by the user is the above-generated first prompt message. Of course, the user can also modify the first prompt message and publish the modified information as the comment message.

[0056] In an example, user Xiaod read the content of the first to tenth chapters of the e-book "Comedy Compendium" recommended by the recommended data, and after reading, published the following comment information on the e-book "Comedy Compendium": "The male protagonist is too powerful". The target behavior type corresponding to the operation behavior of the above user Xiaod is a browse-comment type behavior. In this case, the first prompt message corresponding to the comment component of the recommended data can be generated according to the comment information published by user Xiaod for the e-book "Comedy Compendium". The generated first prompt message can be displayed as the comment information to be commented on in the comment component. When user Xiaod publishes a comment message for the recommended data, he only needs to trigger the comment component to publish the comment message with one key. The comment message published by user Xiaod is the above-generated first prompt message.

[0057] It can be seen that through this embodiment, when the operation behavior is used to browse the multimedia resource and a comment message is published for the multimedia resource, the published comment information can be obtained, and according to the comment information, a first prompt message corresponding to the target component is generated. The target component includes the comment component of the recommended data. Since the first prompt message is the comment information to be commented on corresponding to the comment component, it can improve the convenience of the user's interaction with the comment component, improve the convenience of the user's publishing of the comment message, and improve the user's interaction experience.

[0058] In one embodiment, generating a first prompt message corresponding to the target component according to the comment information includes: Determine the second content related to the comment information in the multimedia resource through a second generative model; Through the second generative model, expand and rewrite the comment information according to the second content to obtain the first prompt message.

[0059] In this embodiment, when generating the first prompt information corresponding to the target component according to the comment information, the second generative model can be first used to determine the second content in the multimedia resource that is relevant to the comment information published by the user. Then, the second generative model is used to expand the comment information published by the user based on the second content in the multimedia resource that is relevant to the comment information published by the user, and the expanded comment information is used as the first prompt information. Among them, the second generative model can include a large language model, and the large language model has the ability to expand text.

[0060] Continuing with the above example, user Xiaod read the content of the first to tenth chapters of the e-book "Comedy Compendium" recommended by the recommended data, and after reading, published the following comment information about the e-book "Comedy Compendium": "The male protagonist is too powerful!". Based on the above comment information, through the large language model, it is recognized that the content in the e-book "Comedy Compendium" that is relevant to the comment information "The male protagonist is too powerful!" is the content related to the male protagonist playing basketball and winning. On the basis of the above content, through the large language model, the comment information published by user Xiaod is expanded. The expanded comment information, that is, the first prompt information, can be exemplified as: "The ability of the male protagonist in the book is too strong. Even when his teammates are extremely unhelpful, he can still win the game. So cool!". Also, this first prompt information is used as the information to be commented on for the comment component corresponding to the recommended data, and the user can publish this first prompt information with one click.

[0061] It can be seen that through this embodiment, the second generative model can be used to determine the second content in the multimedia resource that is relevant to the comment information, and based on the second content, the comment information is expanded to obtain the first prompt information, so that the content of the first prompt information matches the content of the multimedia resource, and the possibility of the user publishing the first prompt information as the comment information of the comment component is increased.

[0062] After determining the first prompt information, in step S108 above, the first prompt information is displayed on the target page; the first prompt information is used to prompt interaction based on the target component and the recommended data. The display position of the first prompt information can be above the target component, below the target component, and the target component can also be displayed in the component box corresponding to the target component. Based on the first prompt information, the user can interact with the recommended data through the target component, such as publishing comment information for the recommended data. When the user interacts with the recommended data, the user can express views and feelings about the multimedia resource recommended in the recommended data, so as to efficiently obtain the views and feelings of the user about the multimedia resource recommended in the recommended data. Furthermore, using the views and feelings published by the user can improve the efficiency of determining high-quality multimedia resources.

[0063] In one example, Figure 4Schematic diagram showing a first prompt message on a target page provided by an embodiment of the present disclosure, as Figure 4 shown, a book promotion post for the e-book "Comedy Compendium" is displayed on the target page, and a like component, a comment component, a favorite component, and a share component are displayed below the book promotion post. Among them, the comment component is the target component, the first prompt message is "Do you think the plot of the female protagonist going to college is wonderful? Let's talk about it together", and the display position of the first prompt message is above the comment component.

[0064] In another example, Figure 5 Schematic diagram showing a first prompt message on a target page provided by another embodiment of the present disclosure, as Figure 5 shown, a book promotion post for the e-book "Comedy Compendium" is displayed on the target page, and a like component, a comment component, a favorite component, and a share component are displayed below the book promotion post. Among them, the comment component is the target component, the first prompt message is "The ability of the male protagonist in the book is too strong. Even when his teammates are extremely unhelpful, he can still win the game. So cool!", the display position of the first prompt message is in the comment box corresponding to the comment component, and the first prompt message is the information to be published corresponding to the comment component. The user can trigger the publish button of the comment component to publish it in one click.

[0065] In one embodiment, the recommended data is the target reply information among the respective reply information for the target topic; the above method further includes: If it is detected that the number of reply information corresponding to the target topic exceeds the quantity threshold, a second prompt message is displayed on the topic page corresponding to the target topic; the second prompt message is used to prompt interaction with the reply information corresponding to the target topic.

[0066] In this embodiment, the recommended data is the target reply information among the respective reply information for the target topic published by the user. Examples of the target topic can be: "I'm out of dramas, please recommend some!" and "I'm out of books, please recommend ancient romantic novels", etc. Based on this, if it is detected that the number of reply information corresponding to the target topic published by the user (the user who publishes the target topic can be the same as or different from the user who performs the operation behavior of the target behavior type) exceeds the pre-set quantity threshold, then, a second prompt message can be displayed on the topic page corresponding to the target topic. Among them, the second prompt message is used to prompt the user who publishes the target topic to interact with the reply information corresponding to the target topic, and the interaction can be liking, commenting, favoriting, etc.

[0067] In an example, Figure 6 Schematic diagram of a topic page provided by an embodiment of the present disclosure, as Figure 6As shown, user Xiaof released a topic with the content "I'm out of books to read, seeking recommendations for comedy books". On the topic page corresponding to this topic, 12 users including user Xiaoa and user Xiaob posted reply messages for the topic released by user Xiaof. Each reply message is a piece of recommendation data, and an example of the form of the recommendation data is a book recommendation post. Among them, the reply message posted by user Xiaoa is a book recommendation post for the e-book "Comedy Compendium"; the reply message posted by user Xiaob is a book recommendation post for the e-book "Comedy Collection". Figure 6 Only the reply messages posted by user Xiaoa and user Xiaob are shown, and the reply messages posted by the other 10 users are not shown. For the reply messages posted by the other users, please refer to Figure 6 the reply messages shown in

[0068] Suppose the preset quantity threshold is 10, and the number of reply messages for the topic released by user Xiaof is 12, which has exceeded the quantity threshold. Then, in this case, a second prompt message can be displayed on the topic page corresponding to the topic released by user Xiaof. The second prompt message can be, for example: "This topic has been replied to by 12 users. Please give them a like with one click.", "This topic has been replied to by 12 users. Click here to collect with one click." The display position of the second prompt message can be at the top or the bottom of the topic page, as long as it does not block the reply messages. The above Figure 6 shown second prompt message is "The topic you released has been replied to by 12 users. Click here to give a like with one click.", and the display position of the second prompt message is at the bottom of the topic page. In addition, a component corresponding to the second prompt message can also be displayed on the topic page, such as Figure 6 shown, the component corresponding to the above second prompt message "The topic you released has been replied to by 12 users. Click here to give a like with one click!" can be a "Give a Like with One Click" component. User Xiaof can click on this "Give a Like with One Click" component to give a like with one click to the reply messages posted by 12 users.

[0069] It can be seen that through this embodiment, when it is detected that the number of reply messages corresponding to the target topic exceeds the quantity threshold, a second prompt message can be displayed on the topic page corresponding to the target topic, enabling users to interact with the reply messages based on the second prompt message, improving the effect of user interaction and the efficiency of determining high-quality multimedia resources.

[0070] It should be noted that the specific content of each book name, example, recommendation information, and prompt message in this embodiment, as well as the content of each attached drawing, are all illustrative examples and do not limit this embodiment. The comment information shown in this embodiment can be segment comments or chapter comments on e-books, and can also be episode comments or whole drama comments on video data.

[0071] In summary, through this embodiment, in the scenario of recommending multimedia resources through recommendation data, when a user performs an operation behavior of a target behavior type on a multimedia resource, a target component can be determined in an interaction component for interacting with the recommendation data based on the target behavior type, and a first prompt message corresponding to the target component can be determined and displayed. The first prompt message is used to prompt the user to interact with the recommendation data based on the target component, so as to obtain the user's views and feelings on the multimedia resources recommended in the recommendation data, and improve the efficiency of determining high-quality multimedia resources.

[0072] Figure 7 FIG. 4 is a schematic structural diagram of an information interaction device provided by an embodiment of the present disclosure. As Figure 7 shown, the device includes: A first display module 701, configured to display a target page; the target page displays recommendation data for recommending multimedia resources; A first determination module 702, configured to determine a target behavior type corresponding to the operation behavior in response to an operation behavior on the multimedia resource based on the recommendation data; A second determination module 703, configured to determine a target component in each interaction component of the target page based on the target behavior type, and determine a first prompt message corresponding to the target component; the interaction component is used to interact with the recommendation data; A second display module 704, configured to display the first prompt message in the target page; the first prompt message is used to prompt interaction with the recommendation data based on the target component.

[0073] Optionally, the first determination module 702 is specifically configured to: if the operation behavior is used to browse the multimedia resource and the browsing duration is less than a duration threshold, determine that the target behavior type is a first type of browsing behavior; if the operation behavior is used to browse the multimedia resource and the browsing duration is not less than the duration threshold, determine that the target behavior type is a second type of browsing behavior; if the operation behavior is used to browse the multimedia resource and post comment information on the multimedia resource, determine that the target behavior type is a browsing and commenting type of behavior; if the operation behavior is used to collect the multimedia resource, determine that the target behavior type is a collection type of behavior.

[0074] Optionally, the second determination module 703 is specifically configured to: obtain a mapping relationship created between the target behavior type and each interaction component, determine the interaction component corresponding to the target behavior type in the mapping relationship as a candidate interaction component; obtain a trigger record of a same-type component for the candidate interaction component, and determine the target component from each candidate interaction component according to the trigger record.

[0075] Optionally, the second determination module 703 is specifically configured to: obtain at least one candidate prompt message configured for the target behavior type and the target component; determine the first prompt message from each of the candidate prompt messages according to the interaction record corresponding to the candidate prompt message; the interaction record is an interaction record based on the interaction between the candidate prompt message and the recommendation data.

[0076] Optionally, the second determination module 703 is specifically configured to: if the operation behavior is used to browse the multimedia resource and the browsing duration is not less than the duration threshold, determine the first content browsed in the multimedia resource; generate the first prompt message corresponding to the target component according to the first content; the target component includes a comment component for the recommendation data; the first prompt message is used to prompt to comment on the recommendation data.

[0077] Optionally, the second determination module 703 is further specifically configured to: determine the knowledge points included in the first content through a first generative model, and generate a knowledge Q&A text corresponding to the knowledge points; generate the first prompt message according to the knowledge Q&A text through the first generative model.

[0078] Optionally, the second determination module 703 is specifically configured to: if the operation behavior is used to browse the multimedia resource and a comment message is published for the multimedia resource, obtain the published comment message; generate the first prompt message corresponding to the target component according to the comment message; the target component includes a comment component for the recommendation data; the first prompt message includes the to-be-commented information corresponding to the comment component.

[0079] Optionally, the second determination module 703 is further specifically configured to: determine the second content related to the comment message in the multimedia resource through a second generative model; rewrite the comment message according to the second content through the second generative model to obtain the first prompt message.

[0080] Optionally, the recommendation data is a target reply message among each reply message for a target topic; the device further includes: a third display module; the third display module is specifically configured to: if it is detected that the number of reply messages corresponding to the target topic exceeds a quantity threshold, display a second prompt message on a topic page corresponding to the target topic; the second prompt message is used to prompt to interact with the reply messages corresponding to the target topic.

[0081] Through this embodiment, in a scenario where multimedia resources are recommended through recommended data, when a user performs an operation behavior of a target behavior type on a multimedia resource, a target component can be determined in an interaction component used to interact with the recommended data based on the target behavior type, and a first prompt message corresponding to the target component can be determined, and the first prompt message can be displayed. The user is prompted to interact with the recommended data based on the target component, so as to obtain the user's views and feelings on the multimedia resources recommended in the recommended data, and improve the efficiency of determining high-quality multimedia resources.

[0082] The information interaction device in the embodiments of the present disclosure can implement each process of the above information interaction method embodiments, and achieve the same effects and functions, which will not be repeated here.

[0083] An embodiment of the present disclosure further provides an electronic device. Figure 8 The following is a schematic structural diagram of the electronic device provided by an embodiment of the present disclosure. As Figure 8 shown, the electronic device may vary greatly due to different configurations or performances, and may include one or more processors 801 and a memory 802. One or more applications or data may be stored in the memory 802. Among them, the memory 802 may be short-term storage or persistent storage. The applications stored in the memory 802 may include one or more modules (not shown in the figure), and each module may include a series of computer-executable instructions in the electronic device. Further, the processor 801 may be configured to communicate with the memory 802 and execute a series of computer-executable instructions in the memory 802 on the electronic device. The electronic device may further include one or more power supplies 803, one or more wired or wireless network interfaces 804, one or more input or output interfaces 805, one or more keyboards 806, etc.

[0084] In a specific embodiment, the electronic device includes a processor; and a memory configured to store computer-executable instructions, and the computer-executable instructions, when executed, cause the processor to implement the following processes: Display a target page; the target page displays recommended data for recommending multimedia resources; In response to an operation behavior on the multimedia resource based on the recommended data, determine the target behavior type corresponding to the operation behavior; Based on the target behavior type, determine a target component in each interaction component of the target page, and determine a first prompt message corresponding to the target component; the interaction component is used to interact with the recommended data; Display the first prompt message on the target page; the first prompt message is used to prompt interaction based on the target component and the recommended data.

[0085] Through this embodiment, in the scenario of recommending multimedia resources through recommended data, when the user performs an operation behavior of a target behavior type on the multimedia resource, the target component can be determined in the interaction component for interacting with the recommended data based on the target behavior type, and the first prompt message corresponding to the target component can be determined and displayed. The first prompt message is used to prompt the user to interact based on the target component and the recommended data, so as to obtain the user's views and feelings on the multimedia resources recommended in the recommended data, and improve the efficiency of determining high-quality multimedia resources.

[0086] The electronic device in the embodiments of the present disclosure can implement each process of the above information interaction method embodiment, and achieve the same effects and functions, which will not be repeated here.

[0087] Another embodiment of the present disclosure further provides a computer-readable storage medium, which is used to store computer-executable instructions. When the computer-executable instructions are executed by a processor, the following processes are implemented: Display a target page; the target page displays recommended data for recommending multimedia resources; In response to an operation behavior on the multimedia resource based on the recommended data, determine the target behavior type corresponding to the operation behavior; Based on the target behavior type, determine a target component in each interaction component of the target page, and determine the first prompt message corresponding to the target component; the interaction component is used to interact with the recommended data; Display the first prompt message on the target page; the first prompt message is used to prompt interaction based on the target component and the recommended data.

[0088] Through this embodiment, in the scenario of recommending multimedia resources through recommended data, when the user performs an operation behavior of a target behavior type on the multimedia resource, the target component can be determined in the interaction component for interacting with the recommended data based on the target behavior type, and the first prompt message corresponding to the target component can be determined and displayed. The first prompt message is used to prompt the user to interact based on the target component and the recommended data, so as to obtain the user's views and feelings on the multimedia resources recommended in the recommended data, and improve the efficiency of determining high-quality multimedia resources.

[0089] The computer-readable storage medium in the embodiments of the present disclosure can implement each process of the above information interaction method embodiment, and achieve the same effects and functions, which will not be repeated here.

[0090] Another embodiment of the present disclosure further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the following processes are implemented: Display a target page; the target page displays recommendation data for recommending multimedia resources; In response to an operation behavior on the multimedia resource based on the recommendation data, determine a target behavior type corresponding to the operation behavior; Based on the target behavior type, determine a target component among the various interactive components on the target page, and determine a first prompt message corresponding to the target component; the interactive components are used to interact with the recommendation data; Display the first prompt message on the target page; the first prompt message is used to prompt interaction with the recommendation data based on the target component.

[0091] Through this embodiment, in the scenario of recommending multimedia resources through recommendation data, when the user performs an operation behavior of a target behavior type on the multimedia resource, based on the target behavior type, a target component can be determined among the interactive components used to interact with the recommendation data, and a first prompt message corresponding to the target component can be determined and displayed. The first prompt message prompts the user to interact with the recommendation data based on the target component, so as to obtain the user's views and feelings on the multimedia resources recommended in the recommendation data, and improve the efficiency of determining high-quality multimedia resources.

[0092] The computer program product in the embodiments of the present disclosure can implement each process of the above information interaction method embodiment, and achieve the same effects and functions, which will not be repeated here.

[0093] In each embodiment of the present disclosure, the computer-readable storage medium includes a read-only memory (ROM for short), a random access memory (RAM for short), a magnetic disk, an optical disk, or the like.

[0094] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software improvements (improvements to method flows). However, with the development of technology, many method flow improvements today can be regarded as direct improvements to hardware circuit structures. Almost all designers obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement to a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (e.g., a field programmable gate array (FPGA)) is such an integrated circuit whose logic function is determined by a user's programming of the device. Designers can program themselves to "integrate" a digital system onto a single PLD, without having to ask a chip manufacturer to design and fabricate a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compilers used in program development and writing. The original code before compilation also has to be written in a specific programming language, which is called a hardware description language (HDL), and there is not just one type of HDL, but many types, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones currently are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also be aware that by simply performing a little logical programming on the method flow using the above-mentioned several hardware description languages and programming it into an integrated circuit, it is easy to obtain the hardware circuit that implements the logical method flow.

[0095] The controller can be implemented in any suitable manner. For example, the controller can take the form of, for example, a microprocessor or a processor and a computer-readable medium storing computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of the controller include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, it is entirely possible to logically program the method steps to enable the controller to be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. to achieve the same functions. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or structures within the hardware component.

[0096] The systems, devices, modules, or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0097] For the convenience of description, when describing the above devices, they are described separately as various units according to their functions. Of course, when implementing the embodiments of the present disclosure, the functions of the various units can be implemented in the same or multiple software and / or hardware.

[0098] Those skilled in the art should understand that one or more embodiments of the present disclosure can be provided as a method, a system, or a computer program product. Therefore, one or more embodiments of the present disclosure can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, one or more embodiments of the present disclosure can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0099] This disclosure is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general purpose computers, special purpose computers, embedded processors, or other programmable data processing devices to produce a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0100] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means that implement the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0102] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements not only includes those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0103] One or more embodiments of the present disclosure may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the present disclosure may also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

[0104] Each embodiment in the present disclosure is described in a progressive manner, and the same or similar parts among the embodiments may be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and the relevant parts may be referred to the description of the method embodiments. The above are only the embodiments of the present disclosure and are not intended to limit the present disclosure. For those skilled in the art, various changes and modifications can be made to the present disclosure. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included within the scope of the claims of the present disclosure.

Claims

1. An information interaction method, characterized in that, Including: Display a target page; The recommended data for recommending multimedia resources is displayed on the target page; In response to an operation behavior for the multimedia resource based on the recommended data, determine the target behavior type corresponding to the operation behavior; Based on the target behavior type, determine a target component among the various interactive components on the target page, and determine the first prompt information corresponding to the target component; The interactive component is used to interact with the recommended data; Display the first prompt information on the target page; The first prompt information is used to prompt interaction with the recommended data based on the target component.

2. The method according to claim 1, wherein The determining the target behavior type corresponding to the operation behavior includes: If the operation behavior is used to browse the multimedia resource and the browsing duration is less than the duration threshold, determine that the target behavior type is the first type of browsing behavior; If the operation behavior is used to browse the multimedia resource and the browsing duration is not less than the duration threshold, determine that the target behavior type is the second type of browsing behavior; If the operation behavior is used to browse the multimedia resource and post comment information for the multimedia resource, determine that the target behavior type is a browsing and commenting behavior; If the operation behavior is used to collect the multimedia resource, determine that the target behavior type is a collection behavior.

3. The method according to claim 1, characterized in that, The determining the target component among the various interactive components on the target page based on the target behavior type includes: Obtain the mapping relationship between the created target behavior type and each interactive component, and determine the interactive component corresponding to the target behavior type in the mapping relationship as the candidate interactive component; Obtain the trigger records of the same-type components for the candidate interactive components, and based on the trigger records, determine the target component among the various candidate interactive components.

4. The method according to claim 1, wherein The determining the first prompt information corresponding to the target component includes: Obtain at least one candidate prompt information configured for the target behavior type and the target component; Based on the interaction records corresponding to the candidate prompt information, determine the first prompt information among the various candidate prompt information; the interaction records are interaction records of interacting with the recommended data based on the candidate prompt information.

5. The method according to claim 1, wherein The determining the first prompt information corresponding to the target component includes: If the operation behavior is used to browse the multimedia resource and the browsing duration is not less than the duration threshold, determine the first content browsed in the multimedia resource; Generate the first prompt information corresponding to the target component according to the first content; the target component includes a comment component for the recommended data; the first prompt information is used to prompt commenting on the recommended data.

6. The method according to claim 5, characterized in that The generating the first prompt information corresponding to the target component according to the first content includes: Through a first generative model, determine the knowledge points included in the first content, and generate a knowledge Q&A text corresponding to the knowledge points; Through the first generative model, generate the first prompt information according to the knowledge Q&A text.

7. The method according to claim 1, wherein The determining the first prompt information corresponding to the target component includes: If the operation behavior is used to browse the multimedia resource and post comment information for the multimedia resource, obtain the posted comment information; Generate the first prompt information corresponding to the target component according to the comment information; the target component includes a comment component for the recommended data; the first prompt information includes the information to be commented corresponding to the comment component.

8. The method according to claim 7, characterized in that, The generating the first prompt information corresponding to the target component according to the comment information includes: Determine the second content related to the comment information in the multimedia resource through a second generative model; Use the second generative model to expand the comment information according to the second content to obtain the first prompt information.

9. The method according to claim 1, characterized in that, The recommended data is the target reply information among the respective reply information for a target topic; the method further includes: If it is detected that the number of reply information corresponding to the target topic exceeds a quantity threshold, display second prompt information on the topic page corresponding to the target topic; the second prompt information is used to prompt interaction with the reply information corresponding to the target topic.

10. An information interaction device, characterized in that, including: A first display module for displaying a target page; The target page displays recommended data for recommending multimedia resources; A first determination module for determining the target behavior type corresponding to the operation behavior in response to an operation behavior for the multimedia resource based on the recommended data; A second determination module for determining a target component among the various interaction components on the target page based on the target behavior type and determining the first prompt information corresponding to the target component; The interaction components are used to interact with the recommended data; A second display module for displaying the first prompt information on the target page; The first prompt information is used to prompt interaction with the recommended data based on the target component.

11. An electronic device, characterized in that, including: A processor; and, A memory configured to store computer-executable instructions, the computer-executable instructions, when executed, cause the processor to implement the method according to any one of claims 1-9 above.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store computer-executable instructions, the computer-executable instructions, when executed by the processor, implement the method according to any one of claims 1-9 above.

13. A computer program product, characterized in that, The computer program product includes a computer program, the computer program, when executed by the processor, implements the method according to any one of claims 1-9 above.

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