A method, apparatus, and storage medium for content recommendation

Abstract

This application discloses a method, device, and storage medium for content recommendation, used to instantly request training recommendations corresponding to consultation information based on a customer service number during operation. This achieves the need for instant problem-solving and instant learning, providing timely and effective training support for target users. The content recommendation method provided in this application embodiment may include: a client obtaining consultation information; the client sending a consultation request to the server corresponding to the customer service number through the customer service number, the consultation request carrying the consultation information, so that the server determines the training recommendations corresponding to the consultation information; the client receiving the training recommendations through the customer service number; and the client displaying the training recommendations to instruct the target user to conduct training according to the training recommendations.

Description

Technical Field

[0001] This application relates to the field of communication technology, specifically to a method, device, and storage medium for content recommendation. Background Technology

[0002] Typically, companies will provide targeted training for their employees to improve their productivity and meet their learning needs.

[0003] Currently, there is a machine learning approach called My Learning that can assign necessary training to employees based on their roles, departments, and business operations. In addition, My Learning also establishes a Learning Bot for sharing, allowing employees to centralize and share training resources with others through the bot, and also expand their learning scope through this learning method.

[0004] However, My Learning's machine learning approach only provides and recommends regular training resources to employees based on their work tasks. But when employees encounter problems in their daily work, they can only accumulate these problems and wait for the next training session to solve them. Therefore, the current learning approach cannot meet the needs of employees for immediate problem-solving and immediate learning when they encounter problems in the work environment, and it cannot provide timely training support for employees. Summary of the Invention

[0005] This application provides a method, device, and storage medium for content recommendation, which is used to instantly request training recommendations corresponding to consultation information based on a customer service number during work, thereby fulfilling the need for instant problem-solving and instant learning, and providing timely and effective training support for target users.

[0006] In view of this, the embodiments of this application provide the following solutions:

[0007] In a first aspect, embodiments of this application provide a content recommendation method, which may include:

[0008] Clients obtain consultation information;

[0009] The client sends an inquiry request to the server corresponding to the customer service number through the customer service number. The inquiry request carries the inquiry information so that the server can determine the training recommendation content corresponding to the inquiry information.

[0010] The client receives the recommended training content through the customer service number;

[0011] The client displays the recommended training content to instruct the target user to undergo training based on the recommended content.

[0012] Secondly, embodiments of this application provide a content recommendation method, which may include:

[0013] The server receives an inquiry request sent by the client through a customer service number, the inquiry request including the inquiry information corresponding to the target user;

[0014] The server determines the recommended training content corresponding to the consultation information;

[0015] The server sends the training recommendation content to the client, so that the client displays the training recommendation content to instruct the target user to conduct training according to the training recommendation content.

[0016] Thirdly, embodiments of this application provide a client, which may include:

[0017] The acquisition unit is used to obtain consultation information;

[0018] The sending unit is used to send an inquiry request to the server corresponding to the customer service number through the customer service number. The inquiry request carries the inquiry information so that the server can determine the training recommendation content corresponding to the inquiry information.

[0019] The first receiving unit is used to receive the training recommendation content through the customer service number;

[0020] The display unit is used to display the training recommendation content to instruct the target user to conduct training based on the training recommendation content.

[0021] Optionally, in conjunction with the third aspect described above, in a first possible implementation, the acquiring unit may include:

[0022] The first receiving module is used to obtain the click instruction of the target user in a preset guidance area, the click instruction carrying the consultation information, and the preset guidance area being located on the conversation interface of the customer service number.

[0023] Optionally, in conjunction with the third aspect described above, in a second possible implementation, the acquisition unit may include:

[0024] The second receiving module is used to receive the inquiry information entered by the target user in the message input box, which is located on the conversation interface of the customer service number.

[0025] Optionally, in conjunction with the third aspect and the first to second possible implementations described above, in the third possible implementation, the consultation information includes resource keywords or information keywords, wherein the resource keywords are used to consult content that is related to the training recommendation content, and the information keywords are used to consult content that is related to the target user and the training recommendation content.

[0026] Optionally, in conjunction with the third aspect above, in a fourth possible implementation, the client may further include:

[0027] The second receiving unit is used to receive group information sent by the server before the obtaining unit obtains the consultation information corresponding to the target user;

[0028] Correspondingly, the acquisition unit includes:

[0029] The third receiving module is used to receive the first consultation message from the target user in the instant messaging group corresponding to the group information. The first consultation message carries the consultation information and is obtained by the target user based on the customer service number.

[0030] Optionally, in conjunction with the third aspect above, in the fifth possible implementation, the consultation information includes the target user's tag attributes and behavioral data, and the group tag or subscription item corresponding to the instant messaging group to which the target user belongs.

[0031] Fourthly, embodiments of this application provide a server, which may include:

[0032] The receiving unit is used to receive a consultation request sent by the client through a customer service number, wherein the consultation request includes consultation information corresponding to the target user;

[0033] A determining unit is used to determine the recommended training content corresponding to the consultation information;

[0034] The sending unit is configured to send the training recommendation content to the client, so that the client displays the training recommendation content to instruct the target user to conduct training according to the training recommendation content.

[0035] Alternatively, in conjunction with the fourth aspect above, in the first possible implementation,

[0036] The sending unit is further configured to send the consultation information to the growth matrix device before the determining unit determines the training recommendation content corresponding to the consultation information, so that the growth matrix determines the training recommendation result based on the consultation information;

[0037] The receiving unit is used to receive the training recommendation results sent by the growth matrix device;

[0038] Correspondingly, the determining unit may include:

[0039] The determination module is used to determine that the training recommendation result is the training recommendation content.

[0040] Fifthly, embodiments of this application provide a computer device, the computer device comprising:

[0041] This includes: input / output (I / O) interfaces, processor, and memory.

[0042] The memory stores program instructions;

[0043] The processor is used to execute program instructions stored in memory to implement the method as described above in the first aspect, any one of the first aspects, the second aspect, and any one of the possible implementations of the second aspect.

[0044] The sixth aspect of this application provides a computer-readable storage medium storing computer-executable instructions for performing a method as described in the first aspect, any one of the first aspect, the second aspect, or any one of the second possible implementations.

[0045] A seventh aspect of this application provides a computer program product containing instructions that, when run on a computer or processor, cause the computer or processor to perform the method of any of the above aspects.

[0046] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0047] In this embodiment, the client sends the target user's inquiry information to the server via a customer service number. The server then determines the corresponding training recommendations based on this information, allowing the client to receive and display the recommended training content via the customer service number, instructing the target user to conduct training and learning accordingly. Because the customer service number provides the client with recommended training content, the target user can instantly request the recommended training content based on the inquiry information during their work, fulfilling the need for immediate resolution and learning, and providing timely and effective training support. Attached Figure Description

[0048] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application.

[0049] Figure 1This is a schematic diagram of the structure of a content recommendation system provided in an embodiment of this application;

[0050] Figure 2 This is a schematic diagram of an embodiment of the content recommendation method provided in this application;

[0051] Figure 3 This is a schematic diagram illustrating a guided consultation provided in an embodiment of this application;

[0052] Figure 4 A schematic diagram illustrating a consultation using resource keywords, provided for an embodiment of this application;

[0053] Figure 5 A schematic diagram illustrating consultation using information keywords, provided as an embodiment of this application;

[0054] Figure 6 This is a schematic diagram illustrating consultation within a group chat, as provided in an embodiment of this application.

[0055] Figure 7 This is a schematic diagram of joining a group provided in the embodiments of this application;

[0056] Figure 8 This is a schematic diagram illustrating push notifications based on group tags provided in the embodiments of this application;

[0057] Figure 9 This is a schematic diagram of the training recommendation content corresponding to the resource keywords provided in the embodiments of this application;

[0058] Figure 10 This is a schematic diagram illustrating the training recommendation content corresponding to the information keywords provided in the embodiments of this application;

[0059] Figure 11a This is a schematic diagram of the training recommendation content provided in the group chat in the embodiments of this application;

[0060] Figure 11b A schematic diagram illustrating the feedback of consultation status provided in an embodiment of this application;

[0061] Figure 12 This is a schematic diagram of one embodiment of the client provided in this application;

[0062] Figure 13 This is a schematic diagram of another embodiment of the client provided in this application;

[0063] Figure 14 This is a schematic diagram of one embodiment of the server provided in this application.

[0064] Figure 15 A schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0065] This application provides a method, device, and storage medium for content recommendation, which is used to instantly request training recommendations corresponding to consultation information based on a customer service number during work, thereby fulfilling the need for instant problem-solving and instant learning, and providing timely and effective training support for target users.

[0066] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0067] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that implementations of the application described herein can be implemented, for example, in sequences other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0068] Typically, companies regularly provide skills training to their employees to meet their learning needs. Currently, machine learning methods like My Learning can regularly assign necessary training to employees based on their roles, departments, and business operations. This approach also establishes a Learning Bot, allowing employees to centralize and share training resources with others, and expand their learning scope through this method. However, existing machine learning methods only provide personalized training resource recommendations and cannot meet the needs of employees for immediate problem-solving and learning when encountering issues in the work environment, thus failing to provide timely training support.

[0069] Therefore, in order to solve the above problems, this application provides a content recommendation method. Please refer to [link / reference]. Figure 1 This is a schematic diagram of the structure of a content recommendation system provided in an embodiment of this application. Figure 1As shown, this content recommendation system includes a client and a server. The client and server interact with each other via a network. Furthermore, the server provides backend services that offer training resources to customer service accounts. These customer service accounts can be understood as a business consultation or message push module within the client. After receiving consultation information, the client sends it to the server through the customer service account, enabling the server to determine the corresponding training recommendations. This allows the client to display the recommended training content, providing timely training support to the target user.

[0070] Secondly, it should be noted that the aforementioned client can be the WeChat Work client, and this client can be installed on terminal devices, including but not limited to mobile phones, mobile terminals, tablets, and laptops. The customer service account is the corresponding WeChat Work customer service account, which is essentially a task bot designed to meet the learning needs of trainees in work scenarios and to facilitate organizational knowledge accumulation, thereby supporting employee training.

[0071] For ease of understanding, this application provides a data processing method. Please refer to [link / reference]. Figure 2 This is a schematic diagram of an embodiment of the method for recommending content provided in this application.

[0072] like Figure 2 As shown, the recommended method provided in this application embodiment may include:

[0073] 201. The client obtains consultation information.

[0074] In this embodiment, the target user will enter the customer service account's chat interface on the client, allowing the client to trigger the customer service account to enter pre-set events, such as "My Recommendations," "My Q&A," "My Appointments," and "Training Resource Search." In this way, the client can obtain the corresponding consultation information within the appropriate event.

[0075] In addition, the consultation information may be resource keywords, information keywords, target user's tag attributes and behavioral data, or group tags or subscription items corresponding to the instant messaging group to which the target user belongs. In practical applications, the consultation information may also include user profile data of the target user, group profile and other information, which will not be specifically described in this application embodiment.

[0076] It should be noted that since target users can interact with the customer service account through one-on-one chat or group chat, the way the client obtains consultation information differs between one-on-one chat and group chat scenarios. Therefore, the following will explain the different situations separately:

[0077] 1) One-on-one chat interaction scenarios.

[0078] In this scenario, the client can obtain the relevant consultation information through different acquisition methods, which will be illustrated with examples below.

[0079] The first method involves the client receiving a click instruction from the target user in a preset guidance area. The click instruction carries the consultation information, and the preset guidance area is located on the conversation interface of the customer service number.

[0080] In other words, when a target user interacts with the customer service account, the preset guidance area on the customer service account's chat interface will provide recommended entry points for "popular modules," and each recommended entry point corresponds to its own guiding text, making it convenient for the target user to quickly and directly inquire about resources based on the guiding text.

[0081] Therefore, once the target user clicks the recommended entry point for the consultation they wish to seek on the session interface, the server will send a corresponding prompt to the client, thus providing the client with the relevant consultation information. Please refer to [link / reference]. Figure 3 This is a schematic diagram illustrating a guided consultation provided in an embodiment of this application. From Figure 3 As can be seen, on the chat interface of the customer service account named "Xiaoji", the "Hot Modules" can include: training resource search, my group chat, my Q&A, my appointment information, my learning plan, my assessment, etc. If the target user wants to inquire about resources related to "Python web crawler", the target user can click on "training resource search". At this time, the server will provide guidance related to "Python web crawler", so that the client can obtain the inquiry information.

[0082] The second method involves the client receiving the inquiry information entered by the target user in a message input box located on the conversation interface of the customer service number.

[0083] In other words, the customer service number will provide input rules on the chat interface. For example, to inquire about the most comprehensive learning resources, one can enter: "resources + keywords"; to inquire about relevant information of a target user, one can enter: "information + keywords". Furthermore, it should be noted that the aforementioned input rules can be formulated according to different actual needs, and this embodiment will not impose specific limitations.

[0084] Therefore, target users can directly enter the consultation information they want to inquire about in the message input box on the chat interface of the customer service number, following the instructions of the input rules.

[0085] For example, to illustrate this using the example of consultation information including resource keywords, please refer to [link / reference]. Figure 4This is a schematic diagram illustrating a consultation using resource keywords, provided in an embodiment of this application. From Figure 4 As can be seen, the resource the target user wants to inquire about is "Python web crawler". Therefore, the resource keyword entered by the target user in the message input box is "resource Python web crawler", and the client can then obtain the inquiry information as "resource Python web crawler". In practical applications, the target user can also enter other resource keywords, such as "resource data analysis", etc., which will not be limited in this embodiment.

[0086] For example, to illustrate this using the example of consultation information including keywords, please refer to [link / reference]. Figure 5 This is a schematic diagram illustrating consultation using information keywords, provided in an embodiment of this application. From Figure 5 As can be seen, the resource the target user wants to inquire about is "appointment," meaning the target user wants to inquire about a resource they have already booked. Therefore, the target user can simply enter the keyword "information appointment" in the message input box, and the client will then receive the consultation information as "information appointment." In practical applications, the target user can also enter other information keywords, such as "information Q&A," etc., which will not be limited in this embodiment.

[0087] It should be noted that the information keywords and resource keywords described above refer to different recommended results. In other words, resource keywords are used to find content relevant to the training recommendations, while information keywords are used to find content relevant to the target user's training recommendations.

[0088] Optionally, in other embodiments, in addition to obtaining consultation information using the first and second consultation methods described above, since the learning needs of different users are not entirely similar or the same, the client can also directly obtain the target user's tag attributes and behavioral data, and use the target user's tag attributes and behavioral data as consultation information.

[0089] For example, if the target user's job title is finance clerk, and the relevant behavioral data of the target user can include actions such as liking, commenting, forwarding, saving, or hovering over cost accounting and general ledger, then the client can use the finance clerk's actions such as liking, commenting, forwarding, saving, or hovering over cost accounting and general ledger as consultation information, enabling the server to provide personalized training recommendations to the target user based on the target user's tag attributes and behavioral data.

[0090] The above mainly explained the process of obtaining consultation information from the perspective of one-on-one chat interaction scenarios. The following describes the solution for clients to obtain consultation information from the perspective of group chat interaction scenarios.

[0091] 2) Interactive scenarios in group chats.

[0092] Optionally, in some embodiments, the information can also be obtained in the following way: before the client obtains the consultation information corresponding to the target user, the method further includes: the client receiving group information sent by the server; correspondingly, the client obtaining consultation information may include: the client receiving a second consultation message input by the target user in the instant messaging group corresponding to the group information, the second consultation message carrying the consultation information, and the second consultation message being obtained by the target user based on the customer service number.

[0093] In other words, when a target user wants to consult via group chat, they can do so by mentioning the customer service number in the instant messaging group. Specifically, the target user enters their initial inquiry message containing their information in the instant messaging group by mentioning the customer service number, and the client can then retrieve the relevant inquiry information.

[0094] It's important to note that before the client receives the consultation information, the server must first determine which instant messaging group the target user belongs to. Once the server identifies the target user's group, it can inform the client of the group information, allowing the client to receive the consultation information from that group. This process not only enables the server to retrieve relevant training recommendations from its database but also allows it to identify other users within the instant messaging group who can provide learning resources or answer questions. The server then collects training recommendations from these other users or recommendations derived from discussions among them, further providing training recommendations to the target user. This ensures that the target user's consultation is answered promptly, significantly satisfying their learning needs.

[0095] For example: Please refer to Figure 6 This is a schematic diagram illustrating consultation within a group chat, as provided in an embodiment of this application. From Figure 6 It can be seen that the target user is "Xiao Wang", and Xiao Wang is a member of "Python Learning and Exchange Group 1". Xiao Wang entered the second inquiry message in "Python Learning and Exchange Group 1" via @BOT: "What is the best Python IDE? Also, are there any recommended tutorials?" In this way, the client can obtain the corresponding inquiry information.

[0096] It should be further clarified that if the server determines that the target user has not joined any instant messaging group, the server needs to check whether the target user has submitted a group join request. If so, the server will add the target user to the corresponding instant messaging group based on the request. It should be understood that a target user wishing to join an instant messaging group can do so through invitation from other users within that group, or by searching for the group and submitting a join request, etc. Specific methods will not be limited in this application. Please refer to [link / reference]. Figure 7 This is a schematic diagram of joining a group provided in an embodiment of this application. From Figure 7 As can be seen, different instant messaging groups correspond to different group tags and belong to different categories. For example, the group tag for "Python Learning and Exchange Group 1" is "Python expert teaching," while the group tag for "Python exchange group" is "Python network analysis," etc. The target user wants to join "Python Learning and Exchange Group 1." In practical applications, there may be other instant messaging groups and corresponding group tags, which will not be specifically limited in this embodiment.

[0097] Optionally, in other embodiments, besides obtaining consultation information by receiving the first consultation message, since the learning needs of group members in different instant messaging groups are not entirely similar or identical, the client can also directly obtain the group tag or subscription item corresponding to the instant messaging group to which the target user belongs. Using the group tag or subscription item as consultation information, the server determines the corresponding training recommendation content based on the group tag or subscription item and then feeds it back to the client, thereby allowing the client to display the training recommendation content within the instant messaging group. For example, for group tags, the server can push some course resources, such as live classes, face-to-face classes, etc.; for subscription items, it can push subscription content, such as weekly reports, selected content, Q&A updates, new member welcome messages, etc. Specific details are not limited in this embodiment.

[0098] For example: Please refer to Figure 8 This is a schematic diagram illustrating push notifications based on group tags provided in an embodiment of this application. From Figure 8 As can be seen, the "Python Learning and Exchange Group 1" displays messages such as "[Course A] is being streamed live! Click to watch http: / / v8.learn.oa.com / act_id=359". In practical applications, other training recommendations could also be included, but this embodiment will not be limited to them.

[0099] 202. The client sends an inquiry request to the server corresponding to the customer service number through the customer service number. The inquiry request carries the inquiry information.

[0100] In this embodiment, since the server can provide backend services for training resources for the customer service number, when the target user interacts with the customer service number through the client to ask questions, make inquiries, etc., the client can carry the inquiry information in the inquiry request after obtaining the inquiry information of the target user, and then consult the server through the customer service number.

[0101] 203. The server determines the recommended training content corresponding to the consultation information.

[0102] In this embodiment, after receiving a consultation request from the client, the server can extract the consultation information carried in the consultation request, and then determine the corresponding training recommendation content from the learning resources or knowledge base based on the consultation information.

[0103] Optionally, in some embodiments, before determining the training recommendation content corresponding to the consultation information, the server sends the consultation information to the growth matrix device, so that the growth matrix device determines the training recommendation result based on the consultation information; the server receives the training recommendation result sent by the growth matrix device; correspondingly, the server determining the training recommendation content corresponding to the consultation information includes: the server determining the training recommendation result as the training recommendation content.

[0104] In this embodiment, since the growth matrix device stores multiple growth matrices, which are formed by the organic combination of multiple online learning products, it provides a learning suite that helps users improve learning efficiency, obtain growth guidance, and solve immediate problems. Therefore, after receiving a client's consultation request, the server can forward the consultation information in the request to the growth matrix device. The growth matrix device then determines the training recommendation result corresponding to the consultation information, and sends the training recommendation result to the server, allowing the server to confirm the training recommendation result as the aforementioned training recommendation content.

[0105] Alternatively, it can be understood that in this embodiment, after receiving a consultation request from the client, the server can directly forward the consultation request to the growth matrix device, which will then extract the relevant consultation information and determine the training recommendation result. The specific sending method will not be limited in this embodiment.

[0106] 204. The server sends training recommendation content to the client.

[0107] In this embodiment, after the server determines the recommended training content, it can send the recommended training content to the client through the customer service number, so that the client can also receive the recommended training content through the customer service number.

[0108] 205. The client displays recommended training content to instruct target users to conduct training based on the recommended content.

[0109] In this embodiment, after the client receives the training recommendation content sent by the server through the customer service number, the client will display the training recommendation content on the conversation interface or interactive interface in the customer service number, so that the target user can learn the training recommendation content by clicking on the training recommendation content on the conversation interface.

[0110] For example, in the aforementioned Figure 4 Based on the described embodiments, please refer to Figure 9 This is a schematic diagram illustrating the training recommendation content corresponding to the resource keywords provided in this embodiment. Figure 9 As can be seen, the training recommendations corresponding to the inquiry information "resource Python web crawler" can include: [Online Courses]: 1. Course A details, 2. Course B details, 3. Course C details; [Face-to-Face Courses]: 1. Course A details, 2. Course S details, 3. Course D details; [Experts]: 1. Q details, 2. W details, 2. E details; [Recommended Group Chats]: 1. Group A details, 2. Group B details, 3. Group C details, etc. In practical applications, other training content recommendations can also be included, but specific details will not be limited here.

[0111] For example, in the aforementioned Figure 5 Based on the described embodiments, please refer to Figure 10 This is a schematic diagram illustrating the training recommendation content corresponding to the information keywords provided in the embodiments of this application. Figure 10 As can be seen, the training recommendations corresponding to the "Information Appointment" inquiry can include: [Appointment]: 1. December 1, 2019; [Face-to-Face Class]: 1. Course Details; 2. December 4, 2019; [Expert]: 2. Details, etc. In practical applications, other training content recommendations can also be included, but this will not be limited here.

[0112] For example: in the aforementioned Figure 6 Based on the described embodiments, please refer to Figure 11a This is a schematic diagram of the training recommendation content provided in the group chat in this embodiment of the application. Figure 11aAs can be seen from Figure 11, within the "Python Learning and Exchange Group 1," the customer service account BOT responded to Xiao Wang's question, such as: "@Xiao Wang, here are some high-quality answers from Xiao Ji to your related questions: 1. kordcang: I recommend the Python 3 modules in the beginner's tutorial; 2. happyhu: I recommend the book 'Dive Into Python 3'; 3. ponyma: I only use Anacoder as my IDE, etc." Additionally, Figure 11 also shows that Xiao Ming, a member of the same "Python Learning and Exchange Group 1," also responded to Xiao Wang's question, such as "@Xiao Wang, I recommend PyCharm as an IDE, and for tutorials, I suggest searching for 'Python: From Beginner to Giving Up'." In practical applications, other training content recommendations can also be included, but specific recommendations will not be limited here.

[0113] In addition, from Figure 11a It can also be seen that after receiving an inquiry from a client, the server can record the inquiry information, allowing it to track the feedback status in real time. This helps the server determine whether the inquiry has been answered, and then sends an invitation message to the client. The client then displays the inquiry feedback information in the customer service chat interface, reminding the target user to provide feedback on the inquiry's status, thus facilitating knowledge retention. Furthermore, the server can also record the target user's behavioral data within instant messaging groups in real time, which can be used for purposes such as organizing talent selection. For example: Please refer to... Figure 11b This is a schematic diagram illustrating the feedback of the consultation status provided in an embodiment of this application. From Figure 11b As can be seen, target users can click the feedback button in [Q&A Edit] to provide feedback on the status of the inquiry. For example, if the inquiry, "What is the best Python IDE? Also, are there any recommended tutorials?", remains unresolved, the target user can click "No"; conversely, if it is resolved, the target user can click "Yes".

[0114] In other words, in some embodiments, after the client sends a consultation request carrying consultation information to the server, the server can also store the consultation information, record whether it has already provided the client with corresponding training recommendations, and then send reminder notifications to the client, such as: appointment time reminders, assessment result reminders, Q&A editing (invitation) reminders, learning plan tracking reminders, popular updates reminders, Q&A updates reminders, etc., which can be referred to as... Figure 11b This should be understood. In practical applications, other reminders and notifications may also be included, but this application embodiment will not be specifically limited to them.

[0115] Additionally, in some embodiments, it is important to understand that after the client displays the recommended training content, the target user also needs to further evaluate that content, i.e., determine the accuracy of the training recommendations provided by the server. If the target user determines that the recommended training content is inaccurate, the client will also collect the user's feedback and report it to the server, so that the server can recommend alternative training content when it receives the same inquiry in the future.

[0116] In this embodiment, the client sends the target user's inquiry information to the server via a customer service number. The server then determines the corresponding training recommendations based on this information, allowing the client to receive and display the recommended training content via the customer service number, instructing the target user to conduct training and learning according to the recommendations. Because the customer service number provides the client with recommended training content, the target user can instantly request the recommended training content corresponding to the inquiry information during their work, fulfilling the need for immediate resolution and learning, and providing timely and effective training support.

[0117] The foregoing primarily describes the solutions provided by the embodiments of this application from a methodological perspective. It is understood that to achieve the above functions, corresponding hardware structures and / or software modules are included to execute each function. Those skilled in the art should readily recognize that, based on the modules and algorithm steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0118] This application embodiment can divide the device into functional modules according to the above method example. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0119] The client 120 in the embodiments of this application will be described in detail below. Please refer to [link / reference]. Figure 12 , Figure 12 This is a schematic diagram of one embodiment of the client 120 provided in this application. The client 120 may include:

[0120] Acquisition unit 1201 is used to acquire consultation information;

[0121] Sending unit 1202 is used to send an inquiry request to the server corresponding to the customer service number through the customer service number. The inquiry request carries the inquiry information so that the server can determine the training recommendation content corresponding to the inquiry information.

[0122] The first receiving unit 1203 is used to receive the training recommendation content through the customer service number;

[0123] Display unit 1204 is used to display the training recommendation content to instruct the target user to conduct training based on the training recommendation content.

[0124] Optionally, in the above Figure 12 Based on the corresponding embodiments, in another embodiment of the client 120 provided in this application, the acquisition unit 1201 may include:

[0125] The first receiving module is used to obtain the click instruction of the target user in a preset guidance area, the click instruction carrying the consultation information, and the preset guidance area being located on the conversation interface of the customer service number.

[0126] Optionally, in the above Figure 12 Based on the corresponding embodiments, in another embodiment of the client 120 provided in this application, the acquisition unit 1201 may include:

[0127] The second receiving module is used to receive the inquiry information entered by the target user in the message input box, which is located on the conversation interface of the customer service number.

[0128] Optionally, in the above Figure 12 Based on the optional embodiments, in another embodiment of the client 120 provided in this application, the consultation information includes resource keywords or information keywords, wherein the resource keywords are used to consult content that is related to the training recommendation content, and the information keywords are used to consult content that is related to the target user and the training recommendation content.

[0129] Optionally, in the above Figure 12 Based on the corresponding embodiments, please refer to Figure 13 , Figure 13 This is a schematic diagram of another embodiment of the client 120 provided in this application. The client 120 may further include:

[0130] The second receiving unit 1205 is used to receive group information sent by the server before the obtaining unit 1201 obtains the consultation information corresponding to the target user;

[0131] Correspondingly, the acquisition unit 1201 includes:

[0132] The third receiving module is used to receive the first consultation message from the target user in the instant messaging group corresponding to the group information. The first consultation message carries the consultation information and is obtained by the target user based on the customer service number.

[0133] Optionally, in the above Figure 12 Based on the corresponding embodiments, in another embodiment of the client 120 provided in this application, the consultation information includes the target user's tag attributes and behavioral data, and the group tag or subscription item corresponding to the instant messaging group to which the target user belongs.

[0134] The above embodiments mainly describe the client 120 in detail from the perspective of modular functional entities. The following embodiments will describe the server 140 from a modular perspective. Please refer to [link / reference]. Figure 14 , Figure 14 This is a schematic diagram of one embodiment of the server 140 provided in this application. The server 140 may include:

[0135] The receiving unit 1401 is used to receive a consultation request sent by the client through a customer service number, wherein the consultation request includes consultation information corresponding to the target user;

[0136] The determining unit 1402 is used to determine the training recommendation content corresponding to the consultation information;

[0137] The sending unit 1403 is used to send the training recommendation content to the client so that the client displays the training recommendation content to instruct the target user to conduct training according to the training recommendation content.

[0138] Optionally, in the above Figure 14 Based on the corresponding embodiments, in another embodiment of the server 140 provided in this application,

[0139] The sending unit 1403 is further configured to send the consultation information to the growth matrix device before the determining unit 1402 determines the training recommendation content corresponding to the consultation information, so that the growth matrix determines the training recommendation result based on the consultation information;

[0140] The receiving unit 1401 is used to receive the training recommendation results sent by the growth matrix device;

[0141] Correspondingly, the determining unit 1402 may include:

[0142] The determination module is used to determine that the training recommendation result is the training recommendation content.

[0143] The client 120 and server 140 in this application embodiment have been described above from the perspective of modular functional entities. The computer device in this application embodiment is described below from the perspective of hardware processing. Figure 15 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. The computer device may include the client 120, server 140, etc. described above. The computer device may vary considerably due to different configurations or performance. The computer device may include at least one processor 1501, a communication line 1507, a memory 1503, and at least one communication interface 1504.

[0144] The processor 1501 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (server IC), or one or more integrated circuits used to control the execution of the program of the present application.

[0145] Communication line 1507 may include a path for transmitting information between the aforementioned components.

[0146] Communication interface 1504 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0147] The memory 1503 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions. The memory can exist independently and be connected to the processor via communication line 1507. The memory can also be integrated with the processor.

[0148] The memory 1503 stores computer execution instructions for implementing the scheme of this application, and its execution is controlled by the processor 1501. The processor 1501 executes the computer execution instructions stored in the memory 1503, thereby implementing the method recommended in the above embodiments of this application.

[0149] Optionally, the computer execution instructions in the embodiments of this application may also be referred to as application code, and the embodiments of this application do not specifically limit this.

[0150] In a specific implementation, as one example, the computer device may include multiple processors, for example... Figure 15 Processors 1501 and 1502 are mentioned. Each of these processors can be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor here can refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0151] In a specific implementation, as one embodiment, the computer device may further include an output device 1505 and an input device 1506. The output device 1505 communicates with the processor 1501 and can display information in various ways. The input device 1506 communicates with the processor 1501 and can receive user input in various ways. For example, the input device 1506 may be a mouse, a touchscreen device, or a sensing device, etc.

[0152] The aforementioned computer device can be a general-purpose device or a special-purpose device. In specific implementations, the computer device can be a desktop computer, a laptop computer, a NAS server, a wireless terminal device, an embedded device, or something similar. Figure 15 A device with a similar structure. The embodiments of this application do not limit the type of computer device.

[0153] In this embodiment of the application, the processor 1501 included in the computer device also has the following functions:

[0154] Clients obtain consultation information;

[0155] The client sends an inquiry request to the server corresponding to the customer service number through the customer service number. The inquiry request carries the inquiry information so that the server can determine the training recommendation content corresponding to the inquiry information.

[0156] The client receives the recommended training content through the customer service number;

[0157] The client displays the recommended training content to instruct the target user to undergo training based on the recommended content.

[0158] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0159] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0160] The unit described as a separate component may or may not be physically separate. The component shown as a unit may or may not be a physical unit; that is, it may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0161] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0162] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0163] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A content recommendation method, characterized in that, include: The client obtains consultation information, which includes the target user's tag attributes and behavioral data, and the group tag or notification item corresponding to the instant messaging group to which the target user belongs; The client sends a consultation request to the server corresponding to the customer service number through the customer service number. The consultation request carries the consultation information so that the server can determine the training recommendation content corresponding to the consultation information. The chat interface of the customer service number contains multiple module entry points. The client receives the recommended training content through the customer service number; The client displays the training recommendation content to instruct the target user to conduct training based on the training recommendation content. The training recommendation content is determined by the server through a growth matrix device, which includes multiple growth matrices, and the growth matrix is ​​formed by combining multiple online learning products. When the client receives status feedback from the user regarding the consultation information, it uploads the status result of the consultation information to the server. The status result includes a resolved status and an unresolved status. Before the client obtains the consultation information corresponding to the target user, the method further includes: When the client receives group information sent by the server, the client correspondingly obtains consultation information, including: The client receives a first consultation message input by the target user in the instant messaging group corresponding to the group information. The first consultation message carries the consultation information and is obtained by the target user based on the customer service number.

2. The method according to claim 1, characterized in that, The client obtains the consultation information corresponding to the target user, including: the client receives a click instruction from the target user in a preset guidance area, the click instruction carrying the consultation information, and the preset guidance area being located on the conversation interface of the customer service number.

3. The method according to claim 1, characterized in that, The client obtains the consultation information corresponding to the target user, including: the client receives the consultation information entered by the target user in a message input box, the message input box being located on the conversation interface of the customer service number.

4. The method according to any one of claims 1-3, characterized in that, The consultation information includes resource keywords or information keywords, wherein the resource keywords are used to consult content that is related to the training recommendation content, and the information keywords are used to consult content that is related to the target user and the training recommendation content.

5. A content recommendation method, characterized in that, include: The server receives a consultation request sent by the client through a customer service number. The consultation request includes consultation information corresponding to the target user. The consultation information is entered by the target user in the instant messaging group corresponding to the group message when the client receives the group message sent by the server. The consultation information includes the target user's tag attributes and behavioral data, the group tag or notification item corresponding to the instant messaging group to which the target user belongs, and the customer service number's conversation interface contains multiple module entry points. The server determines the training recommendation content corresponding to the consultation information. The training recommendation content is determined by the server through a growth matrix device. The growth matrix device includes multiple growth matrices, and the growth matrix is ​​formed by combining multiple online learning products. The server sends the training recommendation content to the client, so that the client displays the training recommendation content to instruct the target user to conduct training according to the training recommendation content; The server receives the status result of the consultation information uploaded by the client. The status result is the information uploaded to the server by the client when it receives the user's status feedback on the consultation information. The status result includes a resolved status and an unresolved status.

6. The method according to claim 5, characterized in that, Before the server determines the recommended training content corresponding to the consultation information, the method further includes: The server sends the consultation information to the growth matrix device, so that the growth matrix device determines the training recommendation result based on the consultation information; the server receives the training recommendation result sent by the growth matrix device. Correspondingly, the server determines the training recommendation content corresponding to the consultation information, including: the server determines the training recommendation result as the training recommendation content.

7. A client application, characterized in that, The client includes: The acquisition unit is used to acquire consultation information, which includes the target user's tag attributes and behavioral data, and the group tag or notification item corresponding to the instant messaging group to which the target user belongs. The sending unit is used to send an inquiry request to the server corresponding to the customer service number through the customer service number. The inquiry request carries the inquiry information so that the server can determine the training recommendation content corresponding to the inquiry information. The conversation interface of the customer service number contains multiple module entries. The first receiving unit is used to receive the training recommendation content through the customer service number; A display unit is used to display the training recommendation content to instruct the target user to conduct training according to the training recommendation content. The training recommendation content is determined by the server through a growth matrix device, which includes multiple growth matrices, and the growth matrix is ​​formed by combining multiple online learning products. The client is also used to upload the status result of the consultation information to the server when the client receives the user's status feedback on the consultation information, and the status result includes a resolved status and an unresolved status; The client includes: The second receiving unit is used to receive group information sent by the server before the obtaining unit obtains the consultation information corresponding to the target user; Correspondingly, the acquisition unit includes: The third receiving module is used to receive the first consultation message from the target user in the instant messaging group corresponding to the group information. The first consultation message carries the consultation information and is obtained by the target user based on the customer service number.

8. The client according to claim 7, characterized in that, The acquisition unit includes: The first receiving module is used to obtain the click instruction of the target user in a preset guidance area, the click instruction carrying the consultation information, and the preset guidance area being located on the conversation interface of the customer service number.

9. The client according to claim 7, characterized in that, The acquisition unit includes: The second receiving module is used to receive the inquiry information entered by the target user in the message input box, which is located on the conversation interface of the customer service number.

10. The client according to any one of claims 7-9, characterized in that, The consultation information includes resource keywords or information keywords, wherein the resource keywords are used to consult content that is related to the training recommendation content, and the information keywords are used to consult content that is related to the target user and the training recommendation content.

11. A server, characterized in that, The server includes: The receiving unit is used to receive a consultation request sent by the client through the customer service number. The consultation request includes consultation information corresponding to the target user. The consultation information is entered by the target user in the instant messaging group corresponding to the group message when the client receives the group message sent by the server. The consultation information includes the target user's tag attributes and behavior data, the group tag or notification item corresponding to the instant messaging group to which the target user is located, and the customer service number's conversation interface contains multiple module entry points. A determining unit is used to determine the training recommendation content corresponding to the consultation information. The training recommendation content is determined by the server through a growth matrix device. The growth matrix device includes multiple growth matrices, and the growth matrix is ​​formed by combining multiple online learning products. A sending unit is configured to send the training recommendation content to the client, so that the client displays the training recommendation content to instruct the target user to perform training according to the training recommendation content; The receiving unit is further configured to receive the status result of the consultation information uploaded by the client. The status result is information uploaded to the server by the client when it receives the user's status feedback on the consultation information. The status result includes a resolved status and an unresolved status.

12. The server according to claim 11, characterized in that, The sending unit is further configured to send the consultation information to the growth matrix device before the determining unit determines the training recommendation content corresponding to the consultation information, so that the growth matrix determines the training recommendation result based on the consultation information; The receiving unit is used to receive the training recommendation results sent by the growth matrix device; Correspondingly, the determining unit includes: The determination module is used to determine that the training recommendation result is the training recommendation content.

13. A computer device, characterized in that, The computer device includes: an input / output (I / O) interface, a processor, and memory. The memory stores program instructions; The processor is used to execute program instructions stored in the memory to perform the method as described in any one of claims 1-4 or 5-6.

14. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on a computer device, the computer device performs the method as described in any one of claims 1-4 or 5-6.

15. A computer program product comprising a computer program, characterized in that, When it is run on a computer device, it causes the computer device to perform the method as described in any one of claims 1-4 or 5-6.

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