Information recommendation method and apparatus, storage medium, and computer device

Abstract

The present invention relates to the technical field of Internet. Disclosed are an information recommendation method and apparatus, a storage medium, and a computer device. The method comprises: in response to an information recommendation operation, sending an information recommendation request, wherein the information recommendation request is used for acquiring at least one piece of first topic information; in response to receiving the first topic information, displaying the first topic information and / or an information input box, wherein the information input box is used for receiving the second topic information input by a user; in response to a trigger operation for the first topic information or an input operation of the second topic information, determining target topic information, and sending the target topic information; and receiving and displaying at least one piece of recommendation information, wherein the recommendation information is matched on the basis of the target topic information, and the recommendation information comprises a recommended merchant and / or a recommended commodity. The method can improve the universality and freshness of recommendation information, and meet the requirement of a user to view new commodities. Moreover, the method has good interactivity.

Description

Information recommendation method, device, storage medium and computer equipment Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to an information recommendation method, device, storage medium and computer equipment. Background Art

[0002] With the continuous development of Internet technology, users' demands for online shopping are becoming more and more diverse. At present, in order to improve the click-through rate and conversion rate of products, e-commerce platforms will recommend various products or merchants to users when they browse products. This allows users to view a variety of products or merchants at any time, so that they can choose the appropriate products according to their needs and place orders.

[0003] In existing technologies, e-commerce platforms primarily recommend products or merchants based on a user's past order history and behavior. This approach often generates recommendations that are highly repetitive and similar to products previously purchased. This approach fails to effectively meet users' desire to try new products, resulting in unsatisfactory recommendations for some users. This limits the breadth of information users can browse and leads to a poor user experience.

[0004] Summary of the Invention

[0005] In view of this, the present application provides an information recommendation method, apparatus, storage medium and computer device, the main purpose of which is to solve the technical problems of limited breadth of recommended information and low user experience.

[0006] According to a first aspect of the present invention, there is provided an information recommendation method, the method comprising:

[0007] The client sends an information recommendation request to the server in response to the information recommendation operation;

[0008] The server obtains at least one first topic information in response to receiving the information recommendation request, and sends the first topic information to the client;

[0009] In response to receiving the first topic information, the client displays the first topic information and / or an information input box, wherein the information input box is used to receive second topic information input by the user;

[0010] The client determines target topic information in response to a triggering operation of the first topic information or an input operation of the second topic information, and sends the target topic information to the server;

[0011] In response to receiving the target topic information, the server matches at least one recommendation information based on the target topic information and sends the recommendation information to the client;

[0012] The client receives and displays the recommendation information, wherein the recommendation information includes recommended merchants and / or recommended products.

[0013] According to a second aspect of the present invention, there is provided an information recommendation method, the method comprising:

[0014] In response to the information recommendation operation, sending an information recommendation request, wherein the information recommendation request is used to obtain at least one first topic information;

[0015] In response to receiving the first topic information, displaying the first topic information and / or an information input box, wherein the information input box is used to receive second topic information input by a user;

[0016] In response to a triggering operation of the first topic information or an input operation of the second topic information, determining target topic information and sending the target topic information;

[0017] Receive and display at least one recommendation information, wherein the recommendation information is obtained based on the matching of the target topic information, and the recommendation information includes a recommended merchant and / or a recommended product.

[0018] According to a third aspect of the present invention, there is provided an information recommendation method, the method comprising:

[0019] In response to receiving the information recommendation request, obtaining at least one first topic information, and sending the first topic information to the client;

[0020] In response to receiving the target topic information, at least one recommendation information is matched based on the target topic information, and the recommendation information is sent to the client, wherein the target topic information is determined based on the trigger operation of the first topic information or the input operation of the second topic information, the second topic information is input through the information input box, and the recommendation information includes recommended merchants and / or recommended products.

[0021] According to a fourth aspect of the present invention, there is provided an information recommendation device, the device comprising:

[0022] a recommendation request response module, configured to send an information recommendation request in response to an information recommendation operation, wherein the information recommendation request is used to obtain at least one first topic information;

[0023] a topic information display module, configured to display the first topic information and / or an information input box in response to receiving the first topic information, wherein the information input box is configured to receive second topic information input by a user;

[0024] a target topic determination module, configured to determine target topic information in response to a triggering operation of the first topic information or an input operation of the second topic information, and send the target topic information;

[0025] The recommendation information display module is used to receive and display at least one recommendation information, wherein the recommendation information is obtained based on the matching of the target topic information, and the recommendation information includes recommended merchants and / or recommended products.

[0026] According to a fifth aspect of the present invention, there is provided an information recommendation device, the device comprising:

[0027] a recommendation request response module, configured to obtain at least one first topic information in response to receiving an information recommendation request, and send the first topic information to the client;

[0028] A recommendation information determination module is used to match at least one recommendation information based on the target topic information in response to receiving the target topic information, and send the recommendation information to the client, wherein the target topic information is determined based on the trigger operation of the first topic information or the input operation of the second topic information, the second topic information is input through the information input box, and the recommendation information includes recommended merchants and / or recommended products.

[0029] According to a sixth aspect of the present invention, there is provided a storage medium storing a computer program, which implements the above-mentioned information recommendation method when executed by a processor.

[0030] According to a seventh aspect of the present invention, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned information recommendation method when executing the program.

[0031] The present invention provides an information recommendation method, apparatus, storage medium, and computer equipment. First, the client sends an information recommendation request to the server in response to an information recommendation operation. The server can obtain at least one first topic information according to the request. Then, the client can receive and display the first topic information and / or display an information input box, wherein the first topic information can be triggered and the information input box can be used to receive the second topic information input by the user. Furthermore, when the first topic information is triggered or the second topic information is input, the client can determine the target topic information based on the triggered first topic information or the input second topic information, and send the target topic information to the server. In response to receiving the target topic information, the server can match the target topic information to obtain at least one recommended information and push it to the client for display. The above-mentioned information recommendation method can determine the target topic information based on the first topic information selected by the user or the second topic information input, and obtain at least one recommended information based on the target topic information matching and push it to the user, so that the recommended information is not limited to the user's past historical order information and user behavior information. At the same time, it is not limited to the search keywords entered by the user, thereby supporting users to flexibly select recommended topics or set new topics according to their interests, and arbitrarily expand the scope of information search through topics, thereby improving the breadth and freshness of recommended information and meeting the user's needs to view new products. In addition, the above-mentioned method has good interactivity and can effectively improve the user's experience of viewing search information. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] FIG1 is a schematic diagram showing a flow chart of an information recommendation method provided by an embodiment of the present invention;

[0033] FIG2 shows a scenario diagram of an information recommendation method provided by an embodiment of the present invention;

[0034] FIG3 shows a scenario diagram of an information recommendation method provided by an embodiment of the present invention;

[0035] FIG4 shows a scenario diagram of an information recommendation method provided by an embodiment of the present invention;

[0036] FIG5 is a schematic diagram showing a scenario of an information recommendation method provided by an embodiment of the present invention;

[0037] FIG6 shows a scenario diagram of an information recommendation method provided by an embodiment of the present invention;

[0038] FIG7 shows a schematic structural diagram of an information recommendation device provided by an embodiment of the present invention;

[0039] FIG8 shows a schematic structural diagram of another information recommendation device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0041] In one embodiment, as shown in FIG1 , an information recommendation method is provided. The method is described by taking the application of the method to a client and a server as an example, and includes the following steps:

[0042] 101. In response to an information recommendation operation, the client sends an information recommendation request to the server.

[0043] Specifically, a user may initiate an information recommendation operation by viewing an application, refreshing the current page, clicking an information recommendation entry on a page, and so on. In response to the information recommendation operation, the client may send an information recommendation request to the server. In this embodiment, the specific method for the user to initiate the information recommendation operation is not specifically limited.

[0044] 102. In response to receiving the information recommendation request, the server obtains at least one first topic information and sends the first topic information to the client.

[0045] The interaction between the client and the server can be direct or indirect. For example, the client can send a request or information directly to the server and receive response data returned by the server, or it can send a request or information indirectly to the server through a third-party client and / or a third-party server and receive response data returned by the server through the third-party client and / or the third-party server. It is understood that this embodiment does not limit the interaction between the client and the server.

[0046] Specifically, in response to receiving an information recommendation request, the server may obtain at least one first topic information based on a preset topic information acquisition strategy, and send the obtained first topic information to the client. In this embodiment, the acquisition strategy for the first topic information may include at least one of a variety of selection methods, such as random selection, selection based on topic click-through rate, and selection based on the correlation between topic information and user information. The selection strategy and the number of selections for the first topic information may be set according to actual conditions, and this embodiment does not make specific restrictions here. In addition, in response to receiving an information recommendation request, the server may also generate at least one first topic information based on user information and / or scene information, and send the generated first topic information to the client.

[0047] In this embodiment, topic information refers to any sentence related to the search topic, and a word limit can be set. Compared to traditional keyword prompts such as product names, product categories, and discount types, topic information, as a form of textual information, offers greater freedom in text and a more flexible and innovative setting method. This makes it easier to push new product information, thereby improving the effectiveness of information recommendations.

[0048] 103. In response to receiving the first topic information, the client displays the first topic information and / or an information input box, wherein the information input box is used to receive second topic information input by the user.

[0049] Specifically, in response to receiving the first topic information pushed by the server, the client can display the first topic information through a preset component. At the same time, the client can also display an information input box, wherein the information input box can be used to receive the second topic information input by the user. In this embodiment, by displaying the first topic information and / or the information input box, it is convenient for users to input topics of interest by selection and input, thereby increasing the breadth of information recommendations. Compared with the traditional keyword search method, the information recommendation method provided by this embodiment can provide users with a wider range of information recommendations. Users can select or input any topic information based on their own needs, and view the recommended information corresponding to the topic information. Its information recommendation form is novel and the recommended information range is wide.

[0050] 104. The client determines target topic information in response to the triggering operation of the first topic information or the input operation of the second topic information, and sends the target topic information to the server.

[0051] Specifically, the client can respond to the triggering operation of the first topic information and send the triggered first topic information as the target topic information to the server, and can also respond to the input operation of the second topic information and send the input second topic information as the target topic information to the server. In this embodiment, the triggering operation of the first topic information and the input operation of the second topic information cannot usually be completed at the same time, and the client will generate a sequence of execution one after the other when responding to the two operations. For example, when the user sends the first topic information and the second topic information "at the same time", the client can respond to the two operations in succession based on the slight time difference between the two operations, and send the two target topic information to the server respectively; or, when the time difference between the two operations is very small, the client can choose to respond to the former operation and send the topic information corresponding to the former operation as the target topic information to the server.

[0052] 105. In response to receiving the target topic information, the server matches at least one recommendation information based on the target topic information and sends the recommendation information to the client.

[0053] Specifically, after receiving the target topic information, the server can match at least one recommended information in the recommended information library based on the association between the target topic information and the information to be recommended. For example, the server can perform word segmentation processing on the target topic information to obtain at least one word segmentation keyword, and then calculate the correlation between each word segmentation keyword and the recommended information, and filter out at least one recommended information based on the correlation. For another example, the server can also perform semantic recognition based on the target topic information to obtain a semantic recognition result corresponding to the recommended information, and then calculate the correlation between the semantic recognition result and each recommended information in the recommended information library, and filter out at least one recommended information based on the correlation. Furthermore, after filtering out multiple recommended information, the server can also sort each recommended information based on the correlation between the word segmentation keyword or the semantic recognition result and each recommended information, and send the sorted recommended information to the client.

[0054] 106. The client receives and displays the recommendation information, where the recommendation information includes recommended merchants and / or recommended products.

[0055] Specifically, after receiving the recommendation information sent by the server, the client can display each recommendation information in the order in which the recommendation information is arranged. The recommendation information can include multiple types, such as recommended merchants and recommended products. For example, the client can display multiple recommended merchants, multiple recommended products, or alternately display recommended merchants and recommended products. In this embodiment, the client can pre-set the information type, display method, and display quantity of the recommendation information, and can also receive user operations to select or set the information type, display method, and display quantity of the recommendation information.

[0056] The information recommendation method provided in this embodiment is as follows: first, the client sends an information recommendation request to the server in response to the information recommendation operation, and the server can obtain at least one first topic information according to the request. Then, the client can receive and display the first topic information and / or display an information input box, wherein the first topic information can be triggered, and the information input box can be used to receive the second topic information input by the user. Furthermore, when the first topic information is triggered or the second topic information is input, the client can determine the target topic information based on the triggered first topic information or the input second topic information, and send the target topic information to the server. In response to receiving the target topic information, the server can match the target topic information to obtain at least one recommended information and push it to the client for display. The above-mentioned information recommendation method can determine the target topic information based on the first topic information selected by the user or the second topic information input, and obtain at least one recommended information based on the target topic information matching and push it to the user, so that the recommended information is not limited to the user's past historical order information and user behavior information. At the same time, it is not limited to the search keywords entered by the user, thereby supporting users to flexibly select recommended topics or set new topics according to their interests, and arbitrarily expand the scope of information search through topics, thereby improving the breadth and freshness of recommended information and meeting the user's needs to view new products. In addition, the above-mentioned method has good interactivity and can effectively improve the user's experience of viewing search information.

[0057] In one embodiment, the information recommendation method may further include the following steps:

[0058] 201. The client displays an information recommendation entrance on a preset page through a first preset component and / or a second preset component.

[0059] Among them, the information recommendation entrance can be used to respond to the information recommendation operation, send an information recommendation request to the server, display the first preset component at a preset position on the preset page, and / or display the second preset component in the information flow of the preset page.

[0060] Specifically, when a user enters an application to browse information, he can view any page in the application, and in at least one preset page, the client can display the information recommendation entrance through the first preset component and / or the second preset component. When the user clicks on the information recommendation entrance, an information recommendation request can be initiated, thereby entering the subsequent recommendation process. Among them, the preset page can be any page of the application software, such as the main page, the theme venue page, the information recommendation page, etc., and the first preset component and the second preset component can be various forms of components such as label components and bubble components. In this embodiment, there is no specific restriction on the category of the preset page and the design form of the first preset component and the second preset component. This embodiment can improve the interactive performance of the page and the convenience of users initiating information recommendation requests by setting the first preset component and the second preset component in the preset position and information flow of the preset page respectively for displaying the information recommendation entrance, thereby improving the user experience.

[0061] For example, as shown in FIG2 , an application's main page is shown. Referring to FIG2 (1), an information recommendation entry can be displayed at a preset position on the main page through a label component "Smart Ordering". When a user clicks on the label component, an information recommendation request can be initiated and the subsequent information recommendation process can be entered. Further, referring to FIG2 (2), in the information flow of the main page, an information recommendation entry can be displayed through a bubble component "Don't know what to eat?" When a user clicks on the bubble component, an information recommendation request can also be initiated and the subsequent information recommendation process can be entered.

[0062] 202. The client displays at least one first topic information on a preset page through a third preset component.

[0063] The first topic information is used to respond to a trigger operation, determine the first topic information as target topic information, and send the target topic information to the server, and the third preset component is displayed at a preset position on the preset page and / or in the information flow of the preset page. In this embodiment, the third preset component can be displayed in association with the second preset component or the first preset component.

[0064] Specifically, in at least one preset page, the client can also display at least one first topic information through a third preset component. When a user clicks on a certain first topic information, the triggered first topic information can be determined as the target topic information, and then the target topic information can be sent to the server, and this topic can be used as the first search topic to enter the subsequent recommendation process. Among them, the preset page can be any page of the application software, such as the main page, the theme venue page, the information recommendation page, etc., and the third preset component can be a label component, a bubble component, or other components in various forms. In this embodiment, there is no specific restriction on the category of the preset page and the design form of the third preset component. This embodiment can improve the interactive performance of the page and the convenience of users initiating information recommendation requests by setting the third preset component in the preset position and information flow of the preset page for displaying the first topic information, making it easier for users to understand the information search function, thereby improving the usability of the information search function.

[0065] For example, referring to FIG2 (2), in the information flow of the main page of an application, multiple first topic information can be displayed through bubble components, such as "Fat Loss and Muscle Gain Package Plan", "What to Eat for Friends' Dinner Party", etc. When a user clicks on a topic, the triggered topic information can be determined as the target topic information, and the target topic information can be sent to the server so that the server can match the recommended information according to the triggered topic information, thereby entering the subsequent information recommendation process.

[0066] The above embodiment can improve the interactive performance of the page and the convenience of users initiating information recommendation requests by setting the first preset component, the second preset component and the third preset component in the preset position and information flow of the preset page to display the information recommendation entrance and the first topic information, making it easier for users to understand the information search function, thereby improving the usability of the information search function and user experience.

[0067] In one embodiment, the above-mentioned step 202 can be specifically implemented through the following steps: the client displays multiple first topic information on a preset page through a third preset component, wherein the multiple first topic information is scrolled along a preset direction, and / or the multiple first topic information is scrolled along a direction corresponding to the sliding operation in response to a sliding operation.

[0068] Specifically, the third preset component can display multiple first topic information at the same time, wherein the multiple topic information can be set to active and / or passive scrolling display effects, so that the current page can display more first topic information. In this embodiment, the third preset component can be used simultaneously with the first preset component and / or the second preset component. Through the above method, the convenience of users viewing topic information can be improved, and it is convenient for users to use the information recommendation function. At the same time, through the scrolling display effect, it is also convenient for users to notice the information search function, so that users can view more new products that they have not tried through the information recommendation function during the information browsing process, thereby improving the user experience.

[0069] For example, referring to FIG2 (2), in the information flow of the main page of an application, multiple first topic information can be displayed through bubble components, such as displaying topics such as "Fat Loss and Muscle Gain Package Plan" and "What to Eat for Friends' Dinner Party". When there are too many topics to fully display all the first topic information within the limited space on the current page, a scrolling display effect can be set to enable the multiple first topic information to scroll automatically, or to scroll passively in response to the user's sliding operation, or to combine the automatic and passive scrolling effects for scrolling.

[0070] In one embodiment, the method for responding to the information recommendation operation in step 101 can be implemented by the following steps: the client generates an information recommendation request in response to the trigger operation of the information recommendation entrance displayed in the preset page, and sends the information recommendation request to the server, and / or the client generates an information recommendation request in response to the trigger operation of the first topic information displayed in the preset page, and determines the target topic information based on the triggered first topic information, and then sends the information recommendation request and the target topic information to the server.

[0071] Specifically, a user can initiate an information recommendation operation through the information recommendation portal displayed in the first preset component and / or the second preset component in the preset page, or through any first topic information displayed in the third preset component in the preset page. In this embodiment, when an information recommendation operation is initiated through the first topic information in the third preset component, it can be understood as jumping directly from step 101 to step 105, thereby executing related functions such as matching recommended information based on the target topic information. This process can also be understood as a simplified process of steps 101 to 104.

[0072] For example, referring to Figure 2 (1), the user can initiate an information recommendation operation through the information recommendation entrance corresponding to the label component "Smart Ordering" displayed on the main page to enter the subsequent information recommendation process; referring to Figure 2 (2), the user can also initiate an information recommendation operation through the information recommendation entrance corresponding to the bubble component "Don't know what to eat?" displayed on the main page to enter the subsequent information recommendation process; referring to Figure 2 (2), the user can also initiate an information recommendation operation through the first topic corresponding to the bubble component "Fat Loss and Muscle Gain Package Plan" displayed on the main page, and make this topic the first search topic, thereby entering the subsequent information recommendation process.

[0073] The above embodiment initiates an information recommendation request by responding to the information recommendation entrance displayed in the preset page and / or the trigger operation of the first topic information, which can improve the interactive performance of the page and the convenience of users initiating information recommendation requests, making it easier for users to understand the information search function, thereby improving the usability of the information search function and user experience.

[0074] In one embodiment, the method for obtaining the first topic information in step 102 can be implemented by the following steps: the server randomly selects at least one first topic information from a pre-established first topic database, wherein a plurality of preset topic information are pre-stored in the first topic database, and / or, based on the triggering frequency of each topic information in the first topic database, at least one first topic information is selected in the first topic database, and / or, the server selects at least one first topic information in the first topic database based on the correlation between user information and / or scene information and each topic information in the first topic database, and / or, the server generates at least one first topic information based on user information and / or scene information.

[0075] Specifically, after receiving the information recommendation request, the server can select a preset number of first topic information and send them to the client for display through at least one of a variety of strategies such as random selection, based on the click-through rate of each topic information, and based on the correlation between user information and / or scene information and the topic information. Among them, selecting the first topic information based on the correlation between user information and / or scene information and each topic information in the first topic database refers to selecting at least one first topic information in the first topic database based on the correlation between each topic information and at least one of a variety of information such as topics that the user has previously input and / or selected, information that the user has browsed, historical order information, current time and season, and the business district where the user is located.

[0076] For example, when a user initiates an information recommendation request, the current scenario information is a certain business district on a certain weekday afternoon in August, and the user information indicates that the user has previously selected a topic related to fat loss. In this case, based on this user information and scenario information, the server can select multiple topics from the first topic database, such as "Milk tea for fat loss" and "Cooling herbal tea for summer heat relief," and select the topic with the highest click-through rate as the first topic information and push it to the client, thereby improving the accuracy of the first topic information recommendation. In addition, the server can also randomly select several topics as the first topic information and push them to the client for display, thereby increasing the breadth and interest of the information recommendation.

[0077] In addition, after receiving the information recommendation request, the server may also generate a preset number of first topic information based on user information and / or scenario information. Specifically, the server may generate multiple first topic information based on at least one of a variety of information such as topics previously input and / or selected by the user, information browsed by the user, historical order information, the current time and season, and the business district where the user is located, using a pre-trained topic generation model, and then send the generated first topic information to the client for display. The topic generation model may be trained based on a large natural language model.

[0078] The above embodiments select the first topic information through a combination of multiple strategies, or generate the first topic information through user information and / or scenario information, which can improve the accuracy of recommending the first topic information or increase the breadth of information recommendation, thereby improving the effect of information recommendation.

[0079] In one embodiment, the method of displaying the first topic information and / or the information input box in step 103 can be implemented by the following steps: the client uses the fourth preset component to display the first topic information, and / or displays the icon corresponding to the first topic information, and / or the client displays the information input box, and / or displays the prompt information corresponding to the information input box.

[0080] Specifically, when displaying the first topic information, the client may also display an icon corresponding to the first topic information. For example, when the first topic information is "Milk tea suitable for fat loss," the milk tea icon corresponding to the topic may also be displayed. Furthermore, when displaying the information input box, the client may also display prompt information corresponding to the information input box. For example, when displaying the information input box, the prompt "You can ask me questions about food" may be displayed in the information input box. This approach improves the interactivity of the page and the fun and usability of the information recommendation function, thereby improving the effectiveness of information recommendations.

[0081] For example, as shown in FIG3 , an information recommendation page of an application is shown. In this example, after a user initiates an information recommendation request through the information recommendation portal on the main page as shown in FIG2 , the client can display the information recommendation page as shown in FIG3 . Referring to FIG3 (1) and FIG3 (2), the client can display multiple first topic information and icons corresponding to each first topic information through preset components, and can also display an information input box at a preset position on the information recommendation page, and display the prompt information corresponding to the information input box in the information input box, thereby improving the interactive performance of the page.

[0082] In one embodiment, step 104 can be implemented by the following steps: the client determines the triggered first topic information as the target topic information in response to the triggering operation of the first topic information, or the client determines the input second topic information as the target topic information in response to the input operation of the second topic information, and then the client sends the target topic information to the server and displays the target topic information, and / or dynamically displays the loading component corresponding to the target topic information.

[0083] Specifically, the client can determine the triggered first topic information or the input second topic information as the target topic information and send the target topic information to the server so that the target topic information can serve as the basis for information recommendation. Furthermore, while the server performs semantic recognition and searches for recommended information, the client can display the target topic information and dynamically display the loading component corresponding to the target topic information, thereby increasing the fun of the information recommendation function and improving the user experience.

[0084] For example, referring to Figure 3, when a user clicks on any first topic information in the information recommendation page, such as when the user clicks on the topic "Milk tea that can be drunk for fat loss", the client can determine the triggered topic as the target topic information; or, referring to Figure 4, when a user enters any customized second topic information in the information input box of the current page, such as when the user enters the topic "Cooling tea for summer", the client can determine the entered topic as the target topic information. The client can then send the determined target topic information to the server, and display the target topic information "Milk tea that can be drunk for fat loss" or "Cooling tea for summer" on the information recommendation page, and then dynamically display the loading component "I'm thinking..." corresponding to the target topic information and the corresponding loading progress bar.

[0085] In one embodiment, step 105 can be implemented by the following steps: the server obtains a semantic recognition result based on the target topic information, then recalls a plurality of recommended information based on the semantic recognition result, and finally sorts the plurality of recommended information, and sends the sorted recommended information to the client. In this embodiment, the target topic information can be semantically recognized by a pre-trained semantic recognition model, wherein the semantic recognition result can include a variety of keywords corresponding to the recommended information, for example, the semantically recognized keywords can include category keywords, specification keywords, product description keywords, product evaluation keywords, scene keywords, etc. Based on the semantically recognized keywords, it is convenient to accurately search, filter and sort the recommended information, thereby improving the accuracy of information recommendation.

[0086] Compared with the traditional method of searching for recommended information based on keywords contained in the search statement, the information recommendation method provided by the above embodiment can find recommended information that is closer to the target topic information through semantic recognition. The recommended information is not limited to the keywords in the search statement and can be screened and sorted according to the semantic information implied in the target topic information. Therefore, the accuracy of information recommendation can be effectively improved.

[0087] In one embodiment, step 105 can be implemented by the following steps: the server first obtains at least one keyword based on the target topic information based on a pre-trained semantic recognition model, wherein the keyword includes at least one of category keywords, specification keywords, scene keywords and product description keywords; then, based on the pre-trained information recall model, multiple recommended information are screened out from a pre-established recommendation information library at least based on the category keywords; finally, the multiple recommended information are sorted according to the correlation between the recommended information and at least one of the specification keywords, scene keywords and product description keywords, and at least one recommended information and the arrangement order of the recommended information are determined according to the sorting result.

[0088] In the above embodiment, the server can optimize and train a pre-trained large model (i.e., a large language model or a large natural language model) through a large number of samples in a preset field, thereby obtaining a semantic recognition model, wherein the input of the semantic recognition model is the target topic information and the output of the semantic recognition model is at least one keyword. In this embodiment, the keyword can be at least one of category keywords, specification keywords, scene keywords, and product description keywords. Through these keywords, operations such as searching, filtering, and sorting of recommended information can be performed, so that multiple recommended information corresponding to the target topic information can be found through semantic recognition, including product information and merchant information, etc. Specifically, the server can filter out multiple recommended information from a pre-established recommendation information library based on at least category keywords based on a pre-trained information recall model, wherein the information recall model can also be obtained through large model training. Furthermore, multiple recommended information can be sorted based on the correlation between the recommended information and keywords such as specification keywords, scene keywords, and product description keywords, and at least one recommended information and the arrangement order of the recommended information can be determined based on the sorting results.

[0089] For example, assuming the target topic is "milk tea that's safe to drink for weight loss," semantic recognition of this target topic can yield keywords such as "low-fat," "low-sugar," "sugar-free," "sugar-free," and "milk tea." The keyword "milk tea" is a category keyword. Based on this keyword and the other keywords mentioned above, multiple milk tea products related to the target topic can be screened. The correlation between the specification keywords and product description keywords "low-fat," "low-sugar," "sugar-free," and "sugar-free" and each milk tea product can then be calculated. The screened milk tea products are ranked based on the correlation results. Finally, the milk tea products ranked in the top few positions based on their relevance are selected and sent to the client as recommended information. In the prior art, recommended information is generally searched and matched based on keywords included in the search statement. For keywords not included in the search statement, the search results are significantly worse, or the relevant recommended information is ranked lower, making it difficult for users to notice, resulting in poor information recommendation accuracy. In contrast, this embodiment performs semantic recognition on the target topic to obtain at least one keyword associated with the recommended information, and then recommends information based on the keywords, effectively improving the accuracy of information recommendations.

[0090] The above embodiment performs semantic recognition on the target topic information to obtain keywords corresponding to the recommended information, and searches, filters, and sorts the recommended information based on the keywords. This can improve the relevance of the recommended information to the target topic information, thereby improving the accuracy of the information recommendation. In addition, by performing semantic recognition on arbitrarily selected or input target topic information to obtain recommended information, users can have a high degree of freedom in their search content. As long as the user enters topic information related to a preset field, the corresponding recommended information can be obtained. Compared to traditional keyword searches, the information recommendation method provided by this embodiment can improve the relevance between recommended information and user needs, thereby improving the effectiveness of information recommendation.

[0091] In one embodiment, step 106 can be implemented by the following steps: the client receives at least one recommendation information and displays at least one recommendation information in the form of a list or information stream, and / or the client displays a recommendation information switching component, wherein the recommendation information switching component is used to display recommendation information corresponding to the recommendation information type in response to a selection operation of the recommendation information type, and the recommendation information type includes product type and merchant type.

[0092] Specifically, after receiving the recommendation information sent by the server, the client can display the recommendation information in a variety of ways such as a list or information stream, wherein the recommendation information can be merchant information and / or product information, etc. In addition, the client can also display a recommendation information switching component for switching the type of recommendation information, which can be set to a variety of forms such as a label, a drop-down box, an icon, etc. according to actual conditions. For example, the recommendation information switching component can be set to two labels, "Merchant" and "Product". When the user clicks on the label corresponding to "Merchant", the client can display multiple merchant information through a list; when the user clicks on the label corresponding to "Product", the client can display multiple product information through a list. The above embodiment can improve the richness of the recommendation information by displaying multiple types of recommendation information. At the same time, it can also meet the user's needs for viewing and selecting various types of recommendation information, so as to improve the information recommendation effect.

[0093] For example, as shown in FIG5 , an information recommendation page of an application is shown. In this example, after the user selects any first topic information or enters any second topic information through the information recommendation page shown in FIG3 or FIG4 , the client can display the corresponding recommended information on the information recommendation page shown in FIG5 . Referring to FIG5 (1) and FIG5 (2), the client can display multiple recommended merchants or multiple recommended products in the form of a list or information flow, and can also display a recommended information switching component so that the page can switch the display of merchants and products according to the user's selection operation.

[0094] In one embodiment, the information recommendation method may further include the following steps:

[0095] 107. In response to receiving the information recommendation request, the server obtains at least one third topic information and sends the third topic information to the client.

[0096] 108. In response to receiving the third topic information, the client displays at least one third topic information within a preset range of the information input box and / or displays preset topic prompt information.

[0097] The third topic information is used to determine the third topic information as target topic information in response to a trigger operation and send the target topic information to a server, and the topic prompt information is used to display at least one first topic information in response to a trigger operation.

[0098] Specifically, in response to receiving the information recommendation request, the server can also obtain at least one third topic information and send the third topic information to the client. After the client receives the third topic information, the third topic information can be displayed within the preset range of the information input box. In this embodiment, the third topic information can serve as an effective supplement to the first topic information, providing users with more selectable topics. In addition, the third topic information can be displayed within the preset range of the information input box, so that the user can refer to or select it when entering the second topic information. Through the above method, the page interaction performance can be improved, and the information recommendation efficiency and the breadth of information recommendation can be improved. In addition, the client can also display topic prompt information, and by interacting with the topic prompt information, such as clicking on the topic prompt information, at least one first topic information can be displayed, wherein the display method can be that the page automatically scrolls to the display position corresponding to the first topic information or updates the first topic information in the current page, etc. By setting the topic prompt information, the page interaction performance can be improved and the information recommendation effect can be improved.

[0099] In this embodiment, the client can set the display timing of the third topic information based on actual circumstances. For example, after the user initiates an information recommendation request, the first and third topic information can be displayed on the same page to enrich the user's selection of topic information. Alternatively, after the user selects a first topic information, at least one third topic information can be displayed to prompt the user that more topics can be selected or customized. It is understood that this embodiment does not specifically limit the display timing and display location of the third topic information.

[0100] For example, as shown in FIG6 , an information recommendation page of an application is displayed. In this example, after the user selects any first topic information or enters any second topic information through the information recommendation page as shown in FIG3 or FIG4 , the client can display the recommended information in the information recommendation page as shown in FIG5 . At the same time, at least one third topic information and preset topic prompt information can also be displayed in the information recommendation page as shown in FIG6 . For example, the client can display multiple third topic information such as “Which is the best snail noodle shop” and “Which are the stores with the most repeat customers nearby”. At the same time, it can also display preset topic prompt information such as “Everyone is asking”. Among them, when there is too much third topic information displayed on the page to fully display all the third topic information through the limited position in the current page, a scrolling display effect can be set to enable multiple third topic information to be automatically scrolled and displayed, or it can also be passively scrolled and displayed in response to the user's sliding operation, or it can also combine automatic and passive scrolling effects to scroll and display.

[0101] In one embodiment, the method for obtaining the third topic information in step 107 can be implemented by the following steps: the server randomly selects at least one third topic information from a pre-established second topic database, wherein the second topic database pre-stores multiple preset topic information and / or at least one second topic information input by the user, and / or the server selects at least one third topic information from the second topic database based on the triggering frequency of each topic information in the second topic database, and / or the server selects at least one third topic information from the second topic database based on the correlation between user information and / or scene information and each topic information in the second topic database, and / or the server generates at least one third topic information based on user information and / or scene information.

[0102] Specifically, after receiving the information recommendation request, the server can also select a preset number of third topic information and send them to the client for display through at least one of a variety of strategies such as random selection, based on the click-through rate of each topic information, and based on the correlation between user information and / or scene information and the topic information. Among them, selecting the third topic information based on the correlation between user information and / or scene information and each topic information in the third topic database refers to selecting at least one third topic information in the second topic database based on the correlation between each topic information and at least one of a variety of information such as topics that the user has previously input and / or selected, information that the user has browsed, historical order information, current time and season, and the business district where the user is located. In this embodiment, the topics in the second topic database may overlap with or be completely different from the topics in the first topic database, wherein the topic information in the second topic database can be set according to actual conditions.

[0103] For example, when a user initiates an information recommendation request, the current context is a certain business district on a certain weekday afternoon in August, and the user information indicates that the user has previously entered a topic related to weight loss. Based on this user information and context, the server can select multiple topics from the second topic database, such as "Delicious low-fat milk tea nearby" and "Afternoon tea brands with the most repeat customers," and select the topic with the highest click-through rate as the third topic information and push it to the client, thereby improving the accuracy of the third topic information recommendation. Furthermore, the server can randomly select several topics as the third topic information and push them to the client for display, thereby increasing the breadth of information recommendations.

[0104] In addition, after receiving the information recommendation request, the server may also generate a preset number of third topic information based on user information and / or scenario information. Specifically, the server may generate multiple third topic information based on at least one of a variety of information such as topics previously entered and / or selected by the user, information browsed by the user, historical order information, the current time and season, and the business district where the user is located, using a pre-trained topic generation model. The generated third topic information is then sent to the client for display. The topic generation model may be pre-trained based on a large natural language model.

[0105] The above-mentioned embodiments select the third topic information through a combination of multiple strategies, or generate the third topic information based on user information and / or scenario information, so that the third topic information can be used as an effective supplement to the first topic information, thereby providing users with more topics to choose from, thereby improving the breadth and interest of information recommendations, and thus improving the information recommendation effect.

[0106] In one embodiment, the information recommendation method may further include the following steps:

[0107] 109. In response to the triggering operation of the third topic information, the client determines the triggered third topic information as target topic information and sends the target topic information to the server.

[0108] 110. The client deletes the triggered third topic information and / or updates the third topic information displayed on the current page.

[0109] Specifically, when any third topic information is triggered, the client can determine the triggered third topic information as the target topic information and send it to the server, so that the server can perform semantic recognition and push recommended information based on the target topic information. Then, the client can display the recommended information, and eliminate the display of the triggered third topic information, and / or update the display of the third topic information in the current page. By eliminating the display of the triggered third topic information and / or updating the display of the third topic information in the current page, the untriggered topic information can be automatically added to the current page for viewing by the user, thereby improving the display efficiency and triggering probability of the third topic information, thereby improving the information recommendation effect.

[0110] For example, referring to FIG6 (1), when the user clicks on the third topic information "Which is the best snail noodle shop", the client can determine the topic as the target topic information and send the target topic information to the server. Then, referring to FIG6 (2), the client can eliminate the display of the third topic information "Which is the best snail noodle shop" and automatically fill in the position with the following topic, or the client can also update the third topic information displayed on the current page, that is, replace a batch of third topic information for the user to view and select.

[0111] In one embodiment, the information recommendation method may further include the following steps:

[0112] 111. In response to a backtracking operation on the recommendation information, the client displays at least one first topic information and / or displays at least one target topic information and recommendation information corresponding to the target topic information.

[0113] Specifically, when the user performs operations such as scrolling up and down, sliding left and right, etc. on a page displaying recommended information, the client can respond to the backtracking operation of the recommended information and display historical recommended information and / or display at least one first topic information, so that the user can view all historical recommended information. In this embodiment, a component for viewing historical recommended information can also be displayed on the page, and when the user clicks on the component, a backtracking operation of the recommended information can also be initiated. It can be understood that the method of initiating the backtracking operation can be set according to actual conditions, and this embodiment does not make specific restrictions here. In addition, the information backtracking range can be limited to all information displayed on the current information recommendation page, or it can be limited to all recommended information that the user has browsed within a preset time period, etc., and this embodiment does not make specific restrictions here.

[0114] For example, referring to Figures 3, 5, and 6, when a user selects the topic "Which snail noodle shop is the best?", the user can view the recommended information corresponding to the topic. Furthermore, when the user scrolls back through the current page, the user can view the recommended information corresponding to the historical search topic "Milk tea for fat loss" as shown in Figure 5. When the user further scrolls back through the current page, the user can also view multiple first topic information such as "Milk tea for fat loss" and "What to eat for dinner with friends tonight" as shown in Figure 3, thereby enabling the user to view all recommended information and topic information retrospectively.

[0115] In the above embodiment, the client displays historical recommendation information and / or first topic information in response to the backtracking operation of the recommendation information, which can facilitate users to view past search records, thereby improving the page interaction performance and the convenience of viewing recommended information, and further improving the user experience.

[0116] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. In addition, the numbers corresponding to the various steps in the above embodiments serve only as identifiers and do not limit the order in which the steps are executed. The order in which the steps are executed in each embodiment can be set according to actual circumstances.

[0117] Furthermore, as a specific implementation of the method shown in Figures 1 to 6, this embodiment provides an information recommendation device, as shown in Figure 7, which includes: a recommendation request response module 31, a topic information display module 32, a target topic determination module 33 and a recommendation information display module 34, wherein:

[0118] The recommendation request response module 31 is configured to send an information recommendation request in response to an information recommendation operation, wherein the information recommendation request is used to obtain at least one first topic information;

[0119] The topic information display module 32 is configured to display the first topic information and / or an information input box in response to receiving the first topic information, wherein the information input box is configured to receive second topic information input by a user;

[0120] a target topic determination module 33, configured to determine target topic information in response to a triggering operation of the first topic information or an input operation of the second topic information, and to send the target topic information;

[0121] The recommendation information display module 34 is configured to receive and display at least one recommendation information, wherein the recommendation information is obtained based on the matching of the target topic information, and the recommendation information includes a recommended merchant and / or a recommended product.

[0122] In a specific application scenario, the device also includes a recommendation entry display module 35, which can be used to display an information recommendation entry on a preset page through a first preset component and / or a second preset component, wherein the information recommendation entry is used to respond to an information recommendation operation, send the information recommendation request to the server, and the first preset component is displayed at a preset position of the preset page, and / or the second preset component is displayed in the information flow of the preset page; and / or display at least one first topic information on the preset page through a third preset component, wherein the first topic information is used to respond to a trigger operation, determine the first topic information as the target topic information, and send the target topic information to the server, and the third preset component is displayed at a preset position of the preset page and / or in the information flow of the preset page.

[0123] In a specific application scenario, the recommendation entry display module 35 can be specifically used to display multiple first topic information on the preset page through a third preset component, wherein multiple first topic information are scrolled along a preset direction, and / or multiple first topic information are scrolled along the direction corresponding to the sliding operation in response to a sliding operation.

[0124] In a specific application scenario, the topic information display module 32 can be specifically used to use the fourth preset component to display the first topic information and / or the icon corresponding to the first topic information; and / or display the information input box and / or the prompt information corresponding to the information input box.

[0125] In a specific application scenario, the target topic determination module 33 can be specifically used to determine the triggered first topic information as the target topic information in response to the triggering operation of the first topic information, or the client can determine the input second topic information as the target topic information in response to the input operation of the second topic information; send the target topic information and display the target topic information, and / or dynamically display the loading component corresponding to the target topic information.

[0126] In a specific application scenario, the recommendation information display module 34 can be specifically used to receive at least one of the recommendation information and display at least one of the recommendation information in the form of a list or information flow; and / or display a recommendation information switching component, wherein the recommendation information switching component is used to respond to the selection operation of the recommendation information type and display the recommendation information corresponding to the recommendation information type, and the recommendation information type includes product type and merchant type.

[0127] In a specific application scenario, the topic information display module 32 can also be used to display at least one of the third topic information within a preset range of the information input box in response to receiving the third topic information, and / or display preset topic prompt information, wherein the third topic information is used to respond to a trigger operation, determine the third topic information as the target topic information, and send the target topic information, and the topic prompt information is used to respond to a trigger operation, display at least one of the first topic information.

[0128] In a specific application scenario, the target topic determination module 33 can also be used to respond to the triggering operation of the third topic information, determine the triggered third topic information as the target topic information, and send the target topic information; eliminate the display of the triggered third topic information, and / or update the display of the third topic information in the current page.

[0129] In a specific application scenario, the recommendation information display module 34 can also be used to display at least one first topic information in response to a backtracking operation of the recommendation information, and / or display at least one target topic information and recommendation information corresponding to the target topic information.

[0130] It should be noted that for other corresponding descriptions of the functional units involved in the information recommendation device provided in this embodiment, reference may be made to the corresponding descriptions in FIG. 1 to FIG. 6 , which will not be repeated here.

[0131] Furthermore, as a specific implementation of the method shown in FIG. 1 to FIG. 6 , this embodiment provides an information recommendation device, as shown in FIG. 8 , which includes: a recommendation request response module 41 and a recommendation information determination module 42 , wherein:

[0132] A recommendation request response module 41 is configured to obtain at least one first topic information in response to receiving an information recommendation request, and send the first topic information to the client;

[0133] The recommendation information determination module 42 can be used to respond to receiving the target topic information, match at least one recommendation information based on the target topic information, and send the recommendation information to the client, wherein the target topic information is determined based on the trigger operation of the first topic information or the input operation of the second topic information, the second topic information is input through the information input box, and the recommendation information includes recommended merchants and / or recommended products.

[0134] In a specific application scenario, the recommendation request response module 41 can be specifically used to randomly select at least one first topic information from a pre-established first topic database, wherein a plurality of preset topic information are pre-stored in the first topic database; and / or select at least one first topic information from the first topic database based on the triggering frequency of each of the topic information in the first topic database; and / or select at least one first topic information from the first topic database based on the correlation between user information and / or scene information and each of the topic information in the first topic database; and / or generate at least one first topic information based on user information and / or scene information.

[0135] In a specific application scenario, the recommendation information determination module 42 can be used to obtain a semantic recognition result according to the target topic information, recall a plurality of recommendation information according to the semantic recognition result, and sort the plurality of recommendation information.

[0136] In a specific application scenario, the recommendation information determination module 42 can be specifically used to obtain at least one keyword based on the target topic information based on a pre-trained semantic recognition model, wherein the keyword includes at least one of category keywords, specification keywords, scene keywords and product description keywords; based on a pre-trained information recall model, multiple recommendation information is screened out in a pre-established recommendation information library at least based on the category keywords; based on the correlation between the recommendation information and at least one of the specification keywords, the scene keywords and the product description keywords, multiple recommendation information are sorted, and at least one recommendation information and the arrangement order of the recommendation information are determined according to the sorting result.

[0137] In a specific application scenario, the recommendation request response module 41 may be further configured to obtain at least one third topic information in response to receiving the information recommendation request, and send the third topic information to the client.

[0138] In a specific application scenario, the recommendation request response module 41 can also be used to randomly select at least one third topic information from a pre-established second topic database, wherein the second topic database pre-stores multiple preset topic information and / or at least one second topic information input by a user; and / or selects at least one third topic information from the second topic database based on the triggering frequency of each of the topic information in the second topic database; and / or selects at least one third topic information from the second topic database based on the correlation between user information and / or scene information and each of the topic information in the second topic database; and / or generates at least one third topic information based on user information and / or scene information.

[0139] It should be noted that for other corresponding descriptions of the functional units involved in the information recommendation device provided in this embodiment, reference may be made to the corresponding descriptions in FIG. 1 to FIG. 6 , which will not be repeated here.

[0140] Based on the above methods shown in FIG. 1 to FIG. 6 , this embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the above information recommendation method shown in FIG. 1 to FIG. 6 is implemented.

[0141] Based on this understanding, the technical solution of the present application can be embodied in the form of a software product. The software product to be identified can be stored in a non-volatile storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each implementation scenario of the present application.

[0142] Based on the above-mentioned methods shown in Figures 1 to 6, and the information recommendation device embodiments shown in Figures 7 and 8, in order to achieve the above-mentioned purpose, this embodiment also provides a computer device for information recommendation, which can be specifically a personal computer, server, smart phone, tablet computer, smart watch, or other network device, etc. The computer device includes a storage medium and a processor; the storage medium is used to store computer programs and an operating system; the processor is used to execute the computer program to implement the above-mentioned methods shown in Figures 1 to 6.

[0143] Optionally, the computer device may further include an internal memory, a communication interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a Wi-Fi module, a display, an input device such as a keyboard, etc. Optionally, the communication interface may further include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a Wi-Fi interface), etc.

[0144] Those skilled in the art will understand that the computer device structure for information recommendation provided in this embodiment does not constitute a limitation on the computer device, and may include more or fewer components, or a combination of certain components, or different component arrangements.

[0145] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the computer device hardware and the software resources to be identified, supporting the execution of the information processing program and other software and / or programs to be identified. The network communication module is used to enable communication between components within the storage medium and with other hardware and software in the information processing computer device.

[0146] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform, or by hardware. By applying the technical solution of the present application, first, the client sends an information recommendation request to the server in response to the information recommendation operation, and the server can obtain at least one first topic information according to the request. Then, the client can receive and display the first topic information and / or display an information input box, wherein the first topic information can be triggered and the information input box can be used to receive the second topic information entered by the user. Further, when the first topic information is triggered or the second topic information is entered, the client can determine the target topic information based on the triggered first topic information or the entered second topic information, and send the target topic information to the server. In response to receiving the target topic information, the server can match the target topic information to obtain at least one recommended information and push it to the client for display. Compared with the prior art, the above information recommendation method can support users to flexibly select recommended topics or set new topics according to their points of interest, and arbitrarily expand the scope of information search through topics, thereby improving the breadth and freshness of recommended information and meeting the needs of users to view new products. In addition, the above method has good interactivity and can effectively improve the user's experience of viewing search information.

[0147] Those skilled in the art will understand that the accompanying drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required to implement the present application. Those skilled in the art will understand that the modules in the devices in the implementation scenario can be distributed in the devices of the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more devices different from the implementation scenario. The modules of the above-mentioned implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0148] The serial numbers of the above application are for descriptive purposes only and do not represent the advantages or disadvantages of the implementation scenarios. The above disclosure only discloses several specific implementation scenarios of the present application, but the present application is not limited thereto. Any changes that can be conceived by those skilled in the art should fall within the scope of protection of the present application.

Claims

1. An information recommendation method, characterized in that: The method comprises: The client sends an information recommendation request to the server in response to the information recommendation operation; The server, in response to receiving the information recommendation request, obtains at least one first topic information, and sends the first topic information to the client; In response to receiving the first topic information, the client displays the first topic information and / or an information input box, wherein the information input box is used to receive second topic information input by a user; The client determines target topic information in response to a trigger operation of the first topic information or an input operation of the second topic information, and sends the target topic information to the server; In response to receiving the target topic information, the server matches at least one recommendation information based on the target topic information and sends the recommendation information to the client; The client receives and displays the recommendation information, wherein the recommendation information includes recommended merchants and / or recommended products.

2. The method according to claim 1, characterized in that The method further comprises: The client displays an information recommendation entrance on a preset page through a first preset component and / or a second preset component, wherein the information recommendation entrance is used to send the information recommendation request to the server in response to an information recommendation operation, the first preset component is displayed at a preset position on the preset page, and / or the second preset component is displayed in an information flow on the preset page; and / or The client displays at least one first topic information on a preset page through a third preset component, wherein the first topic information is used to respond to a trigger operation, determine the first topic information as the target topic information, and send the target topic information to the server, and the third preset component is displayed at a preset position of the preset page and / or in the information flow of the preset page.

3. The method according to claim 2, characterized in that The client displays at least one first topic information on a preset page through a third preset component, including: The client displays multiple pieces of the first topic information on the preset page through a third preset component, wherein the multiple pieces of the first topic information are scrolled along a preset direction, and / or the multiple pieces of the first topic information are scrolled along a direction corresponding to the sliding operation in response to a sliding operation.

4. The method according to claim 1, characterized in that: The server obtains at least one first topic information, including: The server randomly selects at least one first topic information from a pre-established first topic database, wherein the first topic database pre-stores a plurality of preset topic information; and / or The server selects at least one first topic information from the first topic database according to the triggering frequency of each of the topic information in the first topic database; and / or The server selects at least one first topic information from the first topic database according to the correlation between the user information and / or the scenario information and each of the topic information in the first topic database; and / or The server generates at least one first topic information according to user information and / or scenario information.

5. An information recommendation method, characterized in that: The method comprises: In response to the information recommendation operation, sending the information recommendation request, wherein the information recommendation request is used to obtain at least one first topic information; In response to receiving the first topic information, displaying the first topic information and / or an information input box, wherein the information input box is used to receive second topic information input by a user; In response to a trigger operation of the first topic information or an input operation of the second topic information, determining target topic information and sending the target topic information; Receive and display at least one recommendation information, wherein the recommendation information is obtained based on the target topic information matching, and the recommendation information includes a recommended merchant and / or a recommended product.

6. An information recommendation method, characterized in that: The method comprises: In response to receiving the information recommendation request, obtaining at least one first topic information, and sending the first topic information to the client; In response to receiving the target topic information, at least one recommendation information is matched based on the target topic information, and the recommendation information is sent to the client, wherein the target topic information is determined based on a trigger operation of the first topic information or an input operation of second topic information, the second topic information is input through an information input box, and the recommendation information includes recommended merchants and / or recommended products.

7. An information recommendation device, characterized in that: The device comprises: A recommendation request response module, configured to send the information recommendation request in response to the information recommendation operation, wherein the information recommendation request is used to obtain at least one first topic information; a topic information display module, configured to display the first topic information and / or an information input box in response to receiving the first topic information, wherein the information input box is configured to receive second topic information input by a user; a target topic determination module, configured to determine target topic information in response to a trigger operation of the first topic information or an input operation of the second topic information, and send the target topic information; The recommendation information display module is used to receive and display at least one recommendation information, wherein the recommendation information is obtained based on the matching of the target topic information, and the recommendation information includes a recommended merchant and / or a recommended product.

8. An information recommendation device, characterized in that: The device comprises: a recommendation request response module, configured to obtain at least one first topic information in response to receiving an information recommendation request, and send the first topic information to the client; A recommendation information determination module is used to respond to receiving the target topic information, match at least one recommendation information based on the target topic information, and send the recommendation information to the client, wherein the target topic information is determined based on a trigger operation of the first topic information or an input operation of second topic information, the second topic information is input through an information input box, and the recommendation information includes recommended merchants and / or recommended products.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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