Application Recommendation Methods, Devices, Electronic Devices, and Readable Storage Media

Abstract

This disclosure provides an application recommendation method, apparatus, electronic device, and readable storage medium, relating to the field of artificial intelligence technology, particularly large-scale models, intelligent recommendation, and intelligent customer service. The specific implementation involves: displaying a customer service page for dialogue interaction between the user and an intelligent customer service representative for a target service; responding to preset triggering conditions in the user's dialogue, displaying the intelligent customer service's first response, which includes recommendation information for the target application corresponding to the target service. This solution effectively enriches the functionality of the intelligent customer service by recommending the target application to the user at appropriate times during the dialogue interaction, thus improving the user experience.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence technology, and in particular to the fields of large models, intelligent recommendation, and intelligent customer service. Specifically, this disclosure relates to an application recommendation method, apparatus, electronic device, and readable storage medium. Background Technology

[0002] With the rapid development of artificial intelligence technology, intelligent customer service systems have been widely used in various service platforms, becoming an important tool for users to interact with service platforms efficiently and automatically.

[0003] Among related technologies, the functions provided by intelligent customer service systems are too limited. Summary of the Invention

[0004] To address at least one of the aforementioned deficiencies, this disclosure provides an application recommendation method, apparatus, electronic device, and readable storage medium.

[0005] According to one aspect of this disclosure, an application recommendation method is provided, the method comprising: Display the customer service page, which is used for dialogue and interaction between users and the intelligent customer service for the target service; In response to the user's conversation meeting preset trigger conditions, the intelligent customer service will display its first response, which includes recommended information about the target application corresponding to the target service.

[0006] As an optional approach, the triggering condition includes at least one of the following: The user's conversation content contains preset categories of conversational intent; The user's conversation contains preset keywords; Within the preset time after the customer service page is accessed, the user does not trigger any input events for dialogue content.

[0007] As an optional method, display the initial response from the intelligent customer service, including: In response to triggering conditions, such as the user's conversation content containing preset categories of conversation intent, recommended information corresponding to the conversation intent is displayed; In response to triggering conditions, such as the presence of preset keywords in the user's conversation, recommended information corresponding to the keywords in the user's conversation is displayed.

[0008] As an alternative approach, the above methods also include: The system displays a second response from the intelligent customer service team. This second response prompts the user to download the target application. It is generated by calling a pre-trained large language model, based on the user's dialogue and a pre-defined description of the target application's functions.

[0009] As an optional method, the recommended information includes download prompts; the methods mentioned above also include: In response to a download prompt, download the target application and display the download progress information.

[0010] As an optional approach, the recommendation information includes a thumbnail of the target application, and the above methods also include: In response to a trigger event on the thumbnail information, a details page is displayed, which shows detailed information about the target application.

[0011] As an alternative approach, the above methods also include: Recommended information for the target application is displayed as a page component at the top and / or bottom of the customer service page.

[0012] As an optional method, recommendation information is published and updated by the provider of the target service.

[0013] As an optional method, the recommended information can be displayed, including: If the recommendation information passes verification and the target application is available, the recommendation information is displayed.

[0014] According to a second aspect of this disclosure, an application recommendation apparatus is provided, the apparatus comprising: The page display module is used to display the customer service page, which is used for dialogue and interaction between users and the intelligent customer service for the target service. The recommendation information display module is used to display the first response from the intelligent customer service when the user's dialogue situation meets the preset trigger conditions. The first response includes recommendation information for the target application corresponding to the target service.

[0015] According to a third aspect of this disclosure, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to at least one of the aforementioned processors; wherein, The memory stores instructions that can be executed by at least one processor, which, when executed by at least one processor, enables the at least one processor to perform the application-recommended method.

[0016] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are used to cause a computer to execute the above-described application recommended method.

[0017] According to a fifth aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described application recommended method.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0019] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure.

[0020] Figure 1 This is a flowchart illustrating an application recommendation method provided in an embodiment of this disclosure.

[0021] Figure 2 , Figure 3 This is a schematic diagram of a customer service page provided in an embodiment of this disclosure.

[0022] Figure 4 This is a schematic diagram of a details page provided for an embodiment of this disclosure.

[0023] Figure 5 This is a schematic diagram of a customer service page provided in an embodiment of this disclosure.

[0024] Figure 6 This is a schematic diagram of the system architecture provided for an embodiment of this disclosure.

[0025] Figure 7 This is a schematic diagram illustrating the overall process of the method provided in the embodiments of this disclosure.

[0026] Figure 8 This is a schematic diagram of the structure of an application recommendation device provided in an embodiment of this disclosure.

[0027] Figure 9 This is a block diagram of an electronic device used to implement the application recommendation method of the embodiments of this disclosure. Detailed Implementation

[0028] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0029] In related technologies, the functions of intelligent customer service systems are generally limited to obtaining user needs through dialogue and interaction, and then collecting relevant clues. These clues can serve as the basis for providing follow-up services to users. The functions provided by intelligent customer service systems in related technologies are too limited, which severely restricts the value of intelligent customer service.

[0030] Intelligent customer service systems are mostly presented in lightweight formats such as web pages or mini-programs. Their knowledge bases are primarily built around frequently asked and common inquiries, providing users with simple and basic responses. Due to the limitations of these formats (web pages, mini-programs, etc.), the responses provided by intelligent customer service systems are often limited to the "information" level, failing to guide users into a more powerful and comprehensive "solution" environment. This creates a fragmented user experience and can easily lead to service interruptions. For example, regarding housing services, when a user inquires about a specific property, the intelligent customer service system can provide basic information about the property, but it cannot support more complex functions such as "virtual reality (VR) property viewing" or property transactions, resulting in users not receiving complete service. Users may need to search for and install corresponding applications (apps) to access more complex services.

[0031] The inventors of this disclosure have discovered that if an intelligent customer service system can provide an application recommendation mechanism, recommending relevant applications to users at appropriate times during the interaction process, users can obtain more complex and complete functions through the applications, thereby improving the integrity of the service chain and providing users with a more coherent user experience.

[0032] Meanwhile, by providing an application recommendation mechanism, the functions of the intelligent customer service system can be effectively enriched, the value of intelligent customer service can be enhanced, and the application can establish a more direct and stable connection with users, which helps to enhance user stickiness and activity.

[0033] The application recommendation methods, apparatuses, electronic devices, and readable storage media provided in this disclosure are intended to solve at least one of the above-mentioned technical problems of the prior art.

[0034] Figure 1 A flowchart illustrating an application recommendation method provided in an embodiment of this disclosure is shown, such as... Figure 1 As shown, the method can mainly include: Step S110: Display the customer service page, which is used for dialogue and interaction between the user and the intelligent customer service for the target service; Step S120: In response to the user's dialogue meeting the preset triggering conditions, the first response content of the intelligent customer service is displayed. The first response content includes the recommendation information of the target application corresponding to the target service.

[0035] As can be seen from the above process, this disclosure displays a customer service page and, during the dialogue interaction between the user and the intelligent customer service for the target service, responds to preset triggering conditions based on the user's dialogue situation by displaying the intelligent customer service's first response. This first response includes recommended information about the target application corresponding to the target service. This solution effectively enriches the functionality of the intelligent customer service by recommending the target application to the user at appropriate times during the dialogue interaction, thus helping to improve the user experience.

[0036] The following describes in detail each step of the above process and the effects that can be further produced, with reference to the embodiments. It should be noted that the terms "first" and "second" involved in this disclosure do not have limitations in terms of size, order, or quantity, but are only used to distinguish them in name. For example, "first response content" and "second response content" are used to distinguish two response contents.

[0037] First, the above step S210, namely "displaying the customer service page, which is used for dialogue and interaction between the user and the intelligent customer service of the target service", will be described in detail with reference to the embodiments.

[0038] Intelligent customer service refers to programs or systems that simulate automated dialogue and interaction between human customer service representatives and users.

[0039] In this embodiment of the disclosure, the intelligent customer service can serve as the front-end interaction interface of the target service, allowing users to consult relevant information or functions of the target service through dialogue with the intelligent customer service.

[0040] A target service typically corresponds to a specific service provider, such as a merchant, organization, or platform. For example, the target service could be a house-finding service provided by a real estate information service platform or a travel service provided by an airline.

[0041] The customer service page is the front-end interface for users to interact with the intelligent customer service system.

[0042] For example, the customer service page can be a webpage (such as an H5 page), a mini-program, or other similar format.

[0043] For example, the customer service page can provide users with a visual dialogue area, which typically includes a message display area, input boxes, and function buttons. The message display area is used to show the dialogue content entered by the user and the intelligent customer service's response. The input boxes are used for users to enter text, voice, or select preset questions. Function buttons may specifically include virtual buttons for sending dialogue content, virtual buttons for uploading attachments, etc.

[0044] The following describes in detail step S220, namely, "in response to the user's dialogue situation meeting the preset triggering conditions, displaying the first reply content of the intelligent customer service, the first reply content including the recommendation information of the target application corresponding to the target service", with reference to the embodiments.

[0045] The target application is a client that provides users with the full functionality of the target service.

[0046] For example, the target application may include, but is not limited to, mobile applications installed on mobile terminals, desktop applications installed on computers, and applications installed on other types of smart terminal devices.

[0047] For example, the target application can be an official client provided by the service provider of the target service, such as the official application provided by a real estate information service platform.

[0048] The dialogue status refers to the specific state of the dialogue as reflected by the user's behavior during the interaction with the intelligent customer service. Real-time analysis of the user's input or interactive behavior on the customer service page can determine whether the dialogue status meets preset triggering conditions.

[0049] When a user's conversation meets the preset triggering conditions, it can be considered an appropriate time to recommend the target application to the user. Then, the recommendation information of the target application can be displayed to the user in the form of intelligent customer service output reply content.

[0050] Recommendation information can be used to describe the attributes and specific functions of a target application, helping users understand the application and thus guiding them to download and use it. Recommendation information can include various forms such as text, images, and videos.

[0051] For example, Figure 2 This is a schematic diagram of a customer service page provided in an embodiment of this disclosure.

[0052] like Figure 2 As shown, the dialogue entered by the user is "I want to rent a room for a month." This dialogue meets the preset trigger conditions, and the intelligent customer service can output recommendation information for the target application. Figure 2 In the example shown, the recommended information specifically includes the target application's name, icon, storage space, version, and a virtual "Download Now" button.

[0053] In this embodiment, the target service can be understood as a business entity. This entity uses intelligent customer service as a "lightweight entry point" and the target application as a "full-function carrier." Users can consult intelligent customer service for information related to the target service. When the user's dialogue meets the triggering conditions, i.e., when an appropriate recommendation opportunity is reached, the intelligent customer service can recommend the target application that better matches the user's needs, thereby better satisfying the user's need to obtain the target application. Simultaneously, it also provides a download entry for the target application, allowing users to easily trigger the download without complex manual searching and downloading processes, simplifying the operation steps and improving user convenience.

[0054] In summary, by combining steps S110 to S120 above, this embodiment of the present disclosure, in response to the preset triggering conditions met during the dialogue interaction between the user and the intelligent customer service, recommends target applications to the user through the intelligent customer service, thereby enriching the functions of the intelligent customer service and enhancing its value.

[0055] In this solution, based on providing users with relevant information about the target service through intelligent customer service, the solution can recommend the target application to the user at appropriate times, enabling the user to easily install and use the target application, thereby obtaining more complex and complete functions of the target service, thus improving the integrity of the service chain and providing users with a more consistent user experience.

[0056] In one alternative embodiment of this disclosure, the triggering condition includes: the user's dialogue content contains a preset category of dialogue intent.

[0057] Among these features, intent recognition can be performed on the user's dialogue content to determine the user's dialogue intent, and then, based on whether the dialogue intent falls into a time-domain preset category, it can be determined whether the current time is an appropriate time to recommend the target application.

[0058] For example, semantic analysis of user-input dialogue content can be performed using a deep learning-based intent classification model, and the content can be categorized into an intent category.

[0059] In this embodiment of the disclosure, a set of categories (i.e. preset categories) can be specified in advance. When the user's dialogue intent belongs to these categories, it is determined that the user may have a need to use the target application, and the current time is an appropriate time to recommend the target application.

[0060] For example, the preset categories may include function consultation, usage problem feedback, etc. That is, when the user's dialogue intent is function consultation, usage problem feedback, etc., a recommendation of the target application can be triggered.

[0061] This solution can accurately identify the timing of recommendations when users express a need to use the target application in their conversational intent, which helps improve recommendation accuracy.

[0062] In one optional manner disclosed herein, the first response from the intelligent customer service is displayed, including: In response to triggering conditions, such as the user's conversation content containing preset categories of conversation intent, recommended information corresponding to the conversation intent is displayed; Specifically, when the triggering condition includes the user's dialogue content containing a preset category of dialogue intent, and the user's dialogue situation meets the triggering condition, that is, when the user's dialogue intent containing a preset category is detected, the recommended information of the target application displayed can correspond to the user's dialogue intent.

[0063] Recommended information corresponds to the user's conversational intent, meaning that the recommended information contains content that can carry over the user's conversational intent, thus achieving effective feedback on the user's conversational intent.

[0064] In this solution, by effectively reflecting the user's dialogue intent in the recommendation information, the recommendation information can be integrated into the dialogue interaction process and presented to the user as part of the solution, rather than simply and abruptly displaying information, thereby helping to improve the accuracy of recommendations.

[0065] For example, when a user's intent is to inquire about a feature, the corresponding recommendation information can focus on describing the inquired feature to stimulate the user's interest in installing the target application and using the corresponding feature. For instance, if the user's intent is specifically to inquire about the timeliness of listings on a real estate service platform, the corresponding recommendation information could include a detailed description of the timeliness of listings on the real estate service platform.

[0066] In one alternative method disclosed herein, the triggering condition includes: the user's conversation content contains preset keywords.

[0067] The preset keywords can be specific terms related to the functions of the target application. For example, for real estate applications, the preset keywords can include "short-term rental" and "VR house viewing".

[0068] When the above keywords appear in a user's conversation, it indicates that the user has expressed a need for a specific function in the target application, and this is an appropriate time to recommend the target application.

[0069] Reference Figure 2In the example, if the user's input contains the keyword "short-term rental," then recommendations for the target application can be displayed.

[0070] This solution can accurately identify the timing of recommendations when a user's conversation contains preset keywords, such as when the user explicitly mentions a feature in the target application, thus helping to improve the accuracy of recommendations for the target application.

[0071] In one optional manner disclosed herein, the first response from the intelligent customer service is displayed, including: In response to triggering conditions, such as the presence of preset keywords in the user's conversation, recommended information corresponding to the keywords in the user's conversation is displayed.

[0072] Specifically, when the triggering condition includes the presence of preset keywords in the user's conversation content, and the user's conversation meets the triggering condition, that is, when the preset keywords are detected in the user's conversation content, the recommended information of the target application displayed can correspond to the keywords contained in the user's conversation content.

[0073] Recommended information corresponds to keywords in the user's conversation, meaning that the recommended information includes descriptions of the functions related to those keywords, thereby highlighting the functions that the user is interested in.

[0074] In this solution, by highlighting the features that users are interested in in the recommendation information, the recommendation information can focus on the user's actual concerns and provide more effective function descriptions, thereby helping to improve the accuracy of recommendations.

[0075] For example, when a user's conversation contains the keyword "VR house viewing," the corresponding recommendation information can emphasize the "VR house viewing" feature to encourage the user's interest in installing the target application and using the corresponding function. In this example, the recommendation information can include a text-based feature description or a video description, such as text and / or a video introducing the "VR house viewing" feature.

[0076] In one optional method of this disclosure, the triggering condition includes: within a preset time period after the customer service page is triggered, the user does not trigger an input event for dialogue content.

[0077] If a user does not enter any dialogue content within the preset time limit after triggering the customer service page, it indicates that the user's needs may be unclear or that they are in a state of "hesitation." In this case, proactively recommending target applications to the user can accurately match the user's real-time state, thereby improving the accuracy of target application recommendations.

[0078] For example, the preset duration can be set according to actual needs, such as 10 seconds.

[0079] For example, Figure 3 This is a schematic diagram of a customer service page provided in an embodiment of this disclosure.

[0080] like Figure 3 As shown, if the user does not enter any dialogue content within the preset time limit of triggering the customer service page, the intelligent customer service can proactively output recommendation information for the target application, thereby improving the accuracy of the target application recommendation.

[0081] In one alternative embodiment of this disclosure, the method further includes: The system displays a second response from the intelligent customer service team. This second response prompts the user to download the target application. It is generated by calling a pre-trained large language model, based on the user's dialogue and a pre-defined description of the target application's functions.

[0082] The intelligent customer service system can output a first response to recommend the target application, and can also output a second response to provide users with richer prompts based on the recommendation information, which helps to improve the accuracy of the target application recommendation.

[0083] In this embodiment of the disclosure, a large language model can be invoked, and the user's dialogue content and the functional description of the target application can be input into the large language model to obtain the second response content output by the large language model.

[0084] The user's dialogue content includes specific dialogue context, enabling the large language model to accurately analyze the user's current inquiry, thereby ensuring that the generated second response is closely related to the user's inquiry.

[0085] The feature description of a target application is a predefined descriptive text used to explain the unique advantages of each feature in the target application. For example, for the "VR house viewing" feature, the feature description is: Provides VR panoramic house viewing, allowing you to obtain a clear, lag-free VR immersive experience.

[0086] The large language model can match the user's dialogue content reflecting the inquiry with the functional description of the target application, thereby filtering out the functional points that can best solve the user's current inquiry and integrating the inquiry and functional points into a smooth recommendation script.

[0087] For example, the second reply could be: "The feature you inquired about has a detailed demonstration in the target application. Click the card below to download and experience it."

[0088] For example, when a user's inquiry is about the timeliness of listings on a real estate service platform, the second response could be, "New listings and price change information will be updated first in the target application. If you want to get first-hand listing information, downloading the target application is your best choice."

[0089] For example, when a user inquires about the "VR house viewing" feature, the second response could be: "Most of our listings support VR panoramic viewing. For a clear, smooth, and immersive VR experience, we recommend that you use the target application."

[0090] For example, such as Figure 2 As shown, when a user inquires about the "short-term rental" function, the second response could be, "We offer short-term rental services, covering xxx cities, and support video viewings for a diverse rental experience," or "You can download our official app to enjoy discounts."

[0091] In this solution, the second response can prioritize answering the user's inquiry and then display richer information about the target application (such as a description of its specific functions). This, combined with the recommendation information in the first response, improves the accuracy of the target application's recommendations.

[0092] In one optional embodiment of this disclosure, the recommended information includes download prompts, and the method further includes: In response to a download prompt, download the target application and display the download progress information.

[0093] The recommended information may include download prompts, which, when triggered, can initiate the download of the target application (installation package).

[0094] For example, such as Figure 2 As shown, the download prompt can be a virtual "Download Now" button or a download link card that can be triggered by clicking.

[0095] During the download process of the target application (installation package), download progress information can be displayed so that users can be aware of the specific download progress.

[0096] For example, such as Figure 4 As shown, the download progress information can be in the form of a progress bar, which intuitively displays the percentage of the downloaded data in the total data size of the target application's installation package.

[0097] This solution provides download prompts in addition to displaying recommended information for the target application, making it easier for users to quickly trigger the download of the target application. This provides a complete interactive link from "recommendation guidance" to "one-click download", which helps to improve the user experience.

[0098] In one alternative embodiment of this disclosure, the recommended information includes a thumbnail information of the target application, and the method further includes: In response to a trigger event on the thumbnail information, a details page is displayed, which shows detailed information about the target application.

[0099] The recommended information may include the target application's thumbnail information. The thumbnail information is the core information of the target application displayed in the form of abbreviations or summaries, such as the application icon and name, key function icons or text (such as "VR house viewing"), the cover image of the key function introduction video, and the application preview image.

[0100] Displaying thumbnail information of the target application, that is, displaying lightweight thumbnail information in the conversation flow between the user and the intelligent customer service, can serve as an "entry point" that can be triggered by the user to display the detailed interface.

[0101] The detailed information displayed on the details page can be far more comprehensive and detailed than the thumbnail information, aiming to provide users with a complete understanding of the target application and thus offer an immersive and information-complete browsing experience.

[0102] Detailed information includes, for example, a complete list and detailed description of the target application's features, a step-by-step introduction to each core function and the specific problems it can solve, multiple high-definition application screenshots or feature demonstration videos, etc.

[0103] For example, such as Figure 3 As shown, the recommendation information includes abbreviations, i.e. Figure 3 The cover image of the feature introduction video or a preview image of the application.

[0104] Figure 4 This is a schematic diagram of a details page provided in an embodiment of this disclosure. When a user triggers thumbnail information (such as by clicking...),... Figure 3 After displaying the cover image of the feature introduction video or the application preview image, you can show... Figure 4 The details page shown can be used to play feature introduction videos or display high-resolution screenshots of the application.

[0105] Figure 4The details page can also include recommendations, which include download prompts (i.e., a virtual "Download Now" button). Users can trigger these prompts (such as by clicking the virtual "Download Now" button) to automatically download the target application, while the download progress information of the target application is displayed on the details page.

[0106] In this solution, by displaying a thumbnail of the target application on the customer service page, core information can be conveyed to the user without excessively affecting the conversation interaction. It can also serve as an interaction entry point to trigger the display of the details page, which conveys comprehensive information about the target application to the user, thus helping to improve the accuracy of the target application recommendation.

[0107] In one alternative embodiment of this disclosure, the method further includes: Recommended information for the target application is displayed as a page component at the top and / or bottom of the customer service page.

[0108] Among them, displaying recommended information as fixed page components at the top and / or bottom of the customer service page is a static, continuous and high-exposure display method. It can be combined with dynamic recommendation strategies that respond to trigger conditions to achieve better display results and improve recommendation accuracy.

[0109] For example, Figure 5 This is a schematic diagram of a customer service page provided in an embodiment of this disclosure.

[0110] Figure 5 The image shows the initial state of the customer service page. At this point, recommended information can be displayed as fixed page components at the top and bottom of the page. The page component at the top displays more comprehensive recommended information. As the conversation progresses, the customer service page moves upwards, and the top page component moves out of view to avoid occupying screen space. The page component at the bottom top displays more concise recommended information (only showing a "Download Now" virtual button). This is a persistent component and does not move with the customer service page, ensuring continuous display and facilitating quick download of the target application for the user.

[0111] In one alternative approach disclosed herein, the recommendation information is published and updated by the provider of the target service.

[0112] The provider of the target service may be a merchant or organization. The provider can configure and publish recommendation information for the target application. The provider can also update the published recommendation information as needed.

[0113] In this solution, by centralizing the authority to publish and update recommendation information to the service provider, it is easier to manage and control the recommendation information in a unified manner, which helps to ensure the accuracy and timeliness of the recommendation information, thereby delivering recommendation information to users more effectively and reliably and improving recommendation accuracy.

[0114] For example, the intelligent customer service system provided in this disclosure can develop subsystems for both the target service provider and the user. The subsystem for the target service provider can support the input, configuration, and management of recommendation information. In this example, the subsystem for the target service provider can provide an interface, which may include a visual configuration entry point. The target service provider can configure recommendation information based on this visual configuration entry point, such as background images for recommendation cards, feature introduction videos, and recommendation text. The subsystem for the user can be used for displaying customer service pages, interactive dialogue, and recommending target applications. The user-facing subsystem can also be configured with a trigger condition library to precisely manage the timing of target application recommendations.

[0115] For example, when publishing recommendation information, the validity of the recommendation information can be verified, and after the verification is passed, the recommendation information is written into the first database, and the status of the recommendation information is updated to enabled.

[0116] For example, after the provider of the target service updates the recommendation information, it will trigger an update of the corresponding recommendation information in the first database. The second database and the first database can be synchronized based on a message queue mechanism.

[0117] For example, Figure 6 This is a schematic diagram of the system architecture provided for an embodiment of this disclosure.

[0118] like Figure 6 As shown, the subsystem for the target service provider can provide an operation page where the provider can log in to enter and query recommendation information. Recommendation information validation verifies the validity of the recommendation information, and upon successful validation, the recommendation information is written as structured data into the first database.

[0119] For example, a target service provider may also offer multiple target services and develop corresponding intelligent customer service and target applications. Binding recommendation information with intelligent customer service refers to linking intelligent customer service corresponding to the same target service with recommendation information, so that the bound recommendation information is displayed during the interaction between the intelligent customer service and the user.

[0120] The user-facing subsystem can maintain a second database, which can be synchronized with the first database based on a message queue mechanism to ensure the accuracy of the recommendation information in the second database.

[0121] The user-facing subsystem can provide a customer service page. The customer service page rendering module is used to render the customer service page. Recommendation information validation verifies the validity of recommended information so that it can be displayed after successful validation. The dialogue module can interact with users based on a question-and-answer knowledge base. The trigger condition library can contain multiple trigger conditions to accurately determine when to recommend the target application. The large language model is used to generate dialogue content, and when the user recommends the target application, it generates a second response to enhance guidance for downloading the target application.

[0122] The provider of the target service can log in to this operation page to enter and query recommendation information. Recommendation information verification checks the validity of the recommendation information, and upon successful verification, the recommendation information is written as structured data into the first database.

[0123] In one alternative manner disclosed herein, the recommendation information is displayed, including: If the recommendation information passes verification and the target application is available, the recommendation information is displayed.

[0124] In this embodiment of the disclosure, before displaying the recommendation information, it is possible to query whether the recommendation information has passed the verification and to verify that the target application is in an available state. If the recommendation information has passed the verification and the target application is in an available state, the recommendation information is displayed to ensure that the recommendation information is effective and accessible, thereby ensuring a smooth user experience.

[0125] For example, when entering recommendation information, its validity can be validated. If the validation passes, the recommendation information is labeled "Enabled" to indicate that the validation has been successful and it is currently enabled. When it is necessary to display the recommendation information, one can directly query whether it has the "Enabled" label to determine whether the validation has passed.

[0126] For example, Figure 7 This is a schematic diagram illustrating the overall process of the method provided in the embodiments of this disclosure.

[0127] like Figure 7 As shown in the figure, the overall process of the method provided in this embodiment may include three parts: the provider of the target service configuring recommendation information, cross-end database synchronization, and intelligent customer service and user interaction.

[0128] In the process of configuring recommendation information for the target service provider, the provider can log in to the operation page, configure the recommendation information for the target application through the operation page, and bind the recommendation information of the target application with the corresponding intelligent customer service. The recommendation information needs to undergo data validity verification; if the data verification fails, an error message is returned. If the data verification passes, the recommendation information is written to the first database, and the status of the recommendation information is updated to enabled.

[0129] In the cross-database synchronization process, when the recommendation information stored in the first database changes, a change notification can be pushed to the message queue. In response to the change notification, the changed recommendation information can be retrieved from the first database, and data consistency verification can be performed. After the data consistency verification passes, the changed recommendation information is written to the second database, completing the synchronization between the first and second databases.

[0130] In the interaction process between intelligent customer service and users, when a user triggers the customer service page, the user's client will load the customer service page. After the customer service page is loaded, a request for recommended information can be initiated to retrieve recommended information from the database. Simultaneously, it will determine whether the recommended information is enabled and whether the target application is available. If the recommended information is not enabled or the target application is unavailable, the recommended information will not be displayed. When the recommended information is enabled and the target application is available, the recommended information can be returned to the user's client and then displayed in the page components at the top and bottom of the customer service page.

[0131] During the user's interaction with the intelligent customer service, the system can capture the conversation content and determine if the conversation meets the triggering conditions. If not, the conversation can continue; if it does, a command to display recommended information can be issued, which will then be output and displayed by the intelligent customer service. Simultaneously, a large language model can be invoked to generate a second response based on the conversation content and preset feature descriptions, enhancing guidance by displaying this second content. After the user triggers a download prompt, the target application can be downloaded automatically.

[0132] The methods provided in this disclosure can be applied to various application scenarios, including but not limited to: scenarios where users interact with intelligent customer service on various service platforms.

[0133] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0134] According to another embodiment, Figure 8 A schematic diagram of the structure of an application recommendation device provided in an embodiment of this disclosure is shown, such as... Figure 8 As shown, the application recommends that the device 800 may include: Page display module 810 is used to display the customer service page, which is used for dialogue and interaction between users and the intelligent customer service of the target service. The recommendation information display module 820 is used to display the first response content of the intelligent customer service in response to the user's dialogue situation meeting the preset trigger conditions. The first response content includes recommendation information of the target application corresponding to the target service.

[0135] As an optional approach, the triggering condition includes at least one of the following: The user's conversation content contains preset categories of conversational intent; The user's conversation contains preset keywords; Within the preset time after the customer service page is accessed, the user does not trigger any input events for dialogue content.

[0136] As an optional method, the recommendation information display module 820, when displaying the first response from the intelligent customer service, is specifically used for: In response to triggering conditions, such as the user's conversation content containing preset categories of conversation intent, recommended information corresponding to the conversation intent is displayed; In response to triggering conditions, such as the presence of preset keywords in the user's conversation, recommended information corresponding to the keywords in the user's conversation is displayed.

[0137] As an alternative, the above-mentioned apparatus further includes a response content generation module (not shown in the figure), used for: The system displays a second response from the intelligent customer service team. This second response prompts the user to download the target application. It is generated by calling a pre-trained large language model, based on the user's dialogue and a pre-defined description of the target application's functions.

[0138] As an optional approach, the recommended information includes download prompts, and the device further includes a target application download module (not shown in the figure) for: In response to a download prompt, download the target application and display the download progress information.

[0139] As an optional approach, the recommendation information includes a thumbnail of the target application, and the aforementioned device also includes a details display module (not shown in the figure) for: In response to a trigger event on the thumbnail information, a details page is displayed, which shows detailed information about the target application.

[0140] As an alternative, the above-mentioned device also includes a page component display module (not shown in the figure), used for: Recommended information for the target application is displayed as a page component at the top and / or bottom of the customer service page.

[0141] As an optional method, recommendation information is published and updated by the provider of the target service.

[0142] As an optional method, the recommendation information display module 820 is specifically used for displaying recommendation information as follows: If the recommendation information passes verification and the target application is available, the recommendation information is displayed.

[0143] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0144] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0145] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0146] Figure 9A schematic block diagram of an example electronic device 900 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0147] like Figure 9 As shown, device 900 includes a computing unit 901, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 902 or a computer program loaded from storage unit 908 into random access memory (RAM) 903. RAM 903 may also store various programs and data required for the operation of device 900. The computing unit 901, ROM 902, and RAM 903 are interconnected via bus 904. Input / output (I / O) interface 905 is also connected to bus 904.

[0148] Multiple components in device 900 are connected to I / O interface 905, including: input unit 906, such as keyboard, mouse, etc.; output unit 907, such as various types of monitors, speakers, etc.; storage unit 908, such as disk, optical disk, etc.; and communication unit 909, such as network card, modem, wireless transceiver, etc. Communication unit 909 allows device 900 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0149] The computing unit 901 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 performs the various methods described above. For example, in some embodiments, the above-described application recommendation methods can be implemented as computer software programs tangibly contained in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed on device 900 via ROM 902 and / or communication unit 909. When the computer program is loaded into RAM 903 and executed by the computing unit 901, one or more steps of method XXX described above can be performed. Alternatively, in other embodiments, the computing unit 901 can be configured to perform method XXX by any other suitable means (e.g., by means of firmware).

[0150] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0151] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0152] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0153] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0154] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0155] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0156] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0157] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. An application recommendation method, comprising: Display a customer service page, which is used for dialogue and interaction between the user and the intelligent customer service for the target service; In response to the user's conversation meeting a preset trigger condition, the intelligent customer service displays the first response content, which includes recommendation information for the target application corresponding to the target service.

2. The method according to claim 1, wherein, The triggering condition includes at least one of the following: The user's dialogue content includes preset categories of dialogue intent; The user's conversation content contains preset keywords; Within a preset time period after the customer service page is triggered, the user does not trigger any input events for dialogue content.

3. The method according to claim 2, wherein, The first response content displayed by the intelligent customer service includes: In response to the triggering condition including the user's dialogue content containing a preset category of dialogue intent, recommended information corresponding to the dialogue intent is displayed; In response to the triggering condition including the user's conversation content containing preset keywords, recommended information corresponding to the keywords contained in the user's conversation content is displayed.

4. The method according to any one of claims 1-3, further comprising: The system displays a second response from the intelligent customer service representative. This second response prompts the user to download the target application. The second response is generated by calling a pre-trained large language model, based on the user's dialogue and a pre-defined description of the target application's functions.

5. The method according to any one of claims 1-4, wherein, The recommendation information includes download prompts, and the method further includes: In response to the triggering event of the download prompt information, the target application is downloaded, and the download progress information of the target application is displayed.

6. The method according to any one of claims 1-5, wherein, The recommendation information includes a thumbnail information of the target application, and the method further includes: In response to a triggering event on the abbreviated information, a details page is displayed, which shows detailed information about the target application.

7. The method according to any one of claims 1-6, further comprising: Recommended information for the target application is displayed as a page component at the top and / or bottom of the customer service page.

8. The method according to any one of claims 1-7, wherein, The recommended information is published and updated by the provider of the target service.

9. The method according to any one of claims 1-8, wherein, The recommended information is displayed, including: In response to the successful verification of the recommendation information and the availability of the target application, the recommendation information is displayed.

10. An application recommendation device, comprising: The page display module is used to display the customer service page, which is used for dialogue and interaction between the user and the intelligent customer service for the target service. The recommendation information display module is used to display the first response content of the intelligent customer service in response to the user's dialogue situation meeting the preset trigger conditions. The first response content includes recommendation information of the target application corresponding to the target service.

11. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.

12. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-9.

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

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