Store information recommendation method, device, and storage medium

Abstract

Embodiments of the present application provide a store information recommendation method and device and a storage medium. In the embodiments of the present application, the media event is integrated into the store recommendation process, more stores related to the media event can be recommended to the user, and the store recommendation is enriched. In addition, when the store is recommended to the user, the user is shown the media store information, the attraction of the store to the user is increased through the media store information, the probability of the user visiting the store is improved, the efficiency of the user obtaining the required goods from the store is improved, and the use experience of the user on the e-commerce application is improved. Furthermore, the exposure rate and user traffic of the store can be increased, and the sales data of the store is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet, and particularly relates to a store information recommendation method and device and a storage medium. BACKGROUND

[0002] In an e-commerce application, there are a large number of stores, and multiple stores sell the same or similar goods. For a consumer user, it is time-consuming and laborious to select a favorite store from a large number of stores, and the shopping experience is poor.

[0003] In order to improve the shopping experience of the consumer user, the existing e-commerce application starts a store recommendation function, and performs personalized store recommendation for the consumer user according to the preference of the consumer user for the goods, which shortens the time of the user shopping in the store to a certain extent.

[0004] However, the store recommendation based on the preference of the consumer user for the goods to a certain extent leads to a relatively closed store discovery path, and the consumer user is difficult to discover more rich stores, thereby reducing the use experience of the e-commerce application. SUMMARY

[0005] Aspects of the present application provide a store information recommendation method, device and storage medium to improve the richness of store recommendation, improve the efficiency of the user obtaining the required goods from the store, and further improve the use experience of the user for the e-commerce application.

[0006] The embodiment of the present application provides a store information recommendation method, comprising: in response to a triggering operation of store recommendation, obtaining user behavior data and / or store sales data of at least one store in a specified period; obtaining a target store associated with a media event from the at least one store according to the user behavior data and / or the store sales data of the at least one store in the specified period; generating media store information of the target store according to the media event associated with the target store, the media store information comprising information associated with the media event; and displaying the media store information of the target store on a first page to recommend the target store to a user.

[0007] The embodiment of the present application also provides a store information recommendation method, comprising: obtaining a target media event occurring in a specified period; determining a target store associated with the target media event from at least one store; generating media store information of the target store according to the target media event, the media store information comprising information associated with the target media event; and displaying the media store information of the target store on a first page to recommend the target store to a user.

[0008] The embodiment of the present application further provides a shop information recommendation method, comprising the following steps: sending a shop recommendation request to a server device in response to a triggering operation of shop recommendation; receiving media information of a target shop returned by the server device, wherein the target shop is a shop associated with a media event and determined by the server device according to user behavior data and / or shop sales data of at least one shop in a specified period, and the media information of the target shop is generated according to the media event associated with the target shop; and displaying the media information of the target shop on a first page to recommend the target shop to a user.

[0009] The embodiment of the present application further provides a shop information recommendation method, comprising the following steps: obtaining user behavior data and / or shop sales data of at least one shop in a specified period in response to a shop recommendation request sent by a terminal device; obtaining a target shop associated with a media event from the at least one shop according to the user behavior data and / or shop sales data of the at least one shop in the specified period; generating media information of the target shop according to the media event associated with the target shop, wherein the media information of the target shop comprises information associated with the media event; and sending the media information of the target shop to the terminal device, so that the terminal device displays the media information of the target shop.

[0010] The embodiment of the present application further provides an electronic device, comprising a memory and a processor; the memory is used for storing a computer program; the processor is coupled with the memory and used for executing the computer program to implement steps in any shop information recommendation method provided by the embodiment of the present application.

[0011] The embodiment of the present application further provides a computer readable storage medium storing a computer program, when the computer program is executed by a processor, the processor can implement steps in any shop information recommendation method provided by the embodiment of the present application.

[0012] In the embodiments of the present application, the target store associated with the media event is determined according to the user behavior data and / or store sales data of the store in a specified period, or the target media event is selected from the media event, and the target store associated with the target media event is determined, the media store information of the target store is generated according to the media event associated with the target store, and the target store is recommended to the user based on the media store information. By integrating the media event into the store recommendation process, more stores related to the media event can be recommended to the user, and the richness of store recommendation is realized. In addition, when the store is recommended to the user, the user is shown the media store information, the attraction of the store to the user is increased through the media store information, the probability of the user visiting the store is improved, which is beneficial to improve the efficiency of the user obtaining the required goods from the store, and then the use experience of the user on the e-commerce application is improved. Furthermore, the exposure rate and user traffic of the store can be increased, and then the sales data of the store is improved. BRIEF DESCRIPTION OF DRAWINGS

[0013] The drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0014] Figure 1 A schematic diagram of a store information recommendation scenario provided by the embodiments of the present application;

[0015] Figure 2a A flowchart of a store information recommendation method provided by the embodiments of the present application;

[0016] Figure 2b A schematic diagram of a store recommendation result page provided by the embodiments of the present application;

[0017] Figure 2c A schematic diagram of another store recommendation result page provided by the embodiments of the present application;

[0018] Figure 2d A schematic diagram of another store recommendation result page provided by the embodiments of the present application;

[0019] Figure 2e A flowchart of another store information recommendation method provided by the embodiments of the present application;

[0020] Figure 2f A schematic diagram of a store aggregation page provided by the embodiments of the present application;

[0021] Figure 3 A flowchart of another store information recommendation method provided by the embodiments of the present application;

[0022] Figure 4A flowchart of another shop information recommendation method provided by an embodiment of the present application is shown in FIG. 6.

[0023] Figure 5a A structural diagram of a shop information recommendation device provided by an embodiment of the present application is shown in FIG. 5.

[0024] Figure 5b A structural diagram of another shop information recommendation device provided by an embodiment of the present application is shown in FIG. 7.

[0025] Figure 5c A structural diagram of another shop information recommendation device provided by an embodiment of the present application is shown in FIG. 8.

[0026] Figure 6 A structural diagram of an electronic device provided by an embodiment of the present application is shown in FIG. 9. DETAILED DESCRIPTION

[0027] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described below in detail with reference to the embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0028] In the traditional shop recommendation process, the shop discovery path is relatively closed, and it is difficult for the consumer user to discover more rich shops, thereby reducing the use experience of the e-commerce application. To solve this technical problem, the embodiments of the present application provide a shop information recommendation method, device and storage medium, which integrate media events into the shop recommendation process, can recommend more shops related to media events to the user, and realize the richness of shop recommendation. In addition, when recommending shops to the user, the user is shown media shop information, the attraction of the shop to the user is increased through the media shop information, the probability of the user visiting the shop is improved, which is beneficial to improving the efficiency of the user obtaining the required goods from the shop, and thus improving the use experience of the user on the e-commerce application. Furthermore, the exposure rate and user traffic of the shop can be increased, and thus the sales data of the shop can be improved.

[0029] The technical solutions provided by the embodiments of the present application will be described in detail below with reference to the drawings.

[0030] Figure 1 A schematic diagram of a shop information recommendation scenario provided by an embodiment of the present application is shown in FIG. 4. Figure 1As shown, in this scenario, terminal device 11a and server device 11b are included. Among them, terminal device 11a can interact with server device 11b through a wired network or a wireless network. For example, the wired network can include coaxial cable, twisted pair and optical fiber, etc., and the wireless network can be a 2G network, a 3G network, a 4G network or a 5G network, a Wireless Fidelity (WIFI) network, etc.

[0031] Optionally, terminal device 11a can be, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a wearable device, a vehicle-mounted device. Server device 11b can be, but is not limited to, a traditional server, a cloud server, a server array or cluster, etc. It should be understood that, Figure 1 The number and product form of terminal device 11a and server device 11b in

[0032] The user can browse the commodity information and store information through the e-commerce application program (Application, APP) installed on the terminal device 11a, and can also select commodity information online, and perform ordering, payment and other operations for the selected commodity. The e-commerce APP can provide multiple pages for the user, such as the first page, the message page, the commodity detail page, the merchant store page, the shopping cart page and various recommendation pages, etc. In the embodiment of the present application, the e-commerce APP can also provide a store recommendation function for the user to recommend a store to the user. In the embodiment of the present application, the store refers to an online store opened by a merchant on the e-commerce APP, which has a management function of commodity information and store information, a display function of commodity information, and a shopping cart function, an ordering payment function, etc. From the page dimension, the store is a page set for managing various pages, such as the store first page, the commodity detail page, the commodity classification page, etc.

[0033] Referring to Figure 1 , the user can initiate a triggering operation of store recommendation on a specific page of the e-commerce APP, and the specific page includes but is not limited to the first page, the commodity detail page or the search page, etc., and the specific page includes a store recommendation function entrance, and the user can initiate the triggering operation of store recommendation through the store recommendation function entrance. Exemplarily, as shown in Figure 1 , the "daily good store" is included in the function navigation area of the first page, which is an example of the store recommendation function entrance, and the user can click the "daily good store" to initiate the triggering operation of store recommendation; or the user can also input "daily good store" in the search bar on the first page, and then click the "search" control to initiate the triggering operation of store recommendation.

[0034] When the user initiates the triggering operation of store recommendation, referring to Figure 1As shown in ①, in response to the triggering operation of the store recommendation, terminal device 11a sends a store recommendation request to server device 11b. (See also...) Figure 1 As shown in ②, server device 11b responds to the store recommendation request and obtains user behavior data and / or store sales data for at least one store within a specified time period. Next, see... Figure 1 As shown in ③, server device 11b obtains the target store for the associated media event from at least one store based on user behavior data and / or store sales data of at least one store within a specified time period. Next, see... Figure 1 As shown in ④, server device 11b generates media-enhanced store information for the target store based on media events associated with the target store. This media-enhanced store information includes information associated with the media events. Next, see... Figure 1 As shown in ⑤, server device 11b sends the media-enabled store information of the target store to terminal device 11a. See also... Figure 1 As shown in ⑥, after receiving the media-based store information of the target store, the terminal device 11a displays the media-based store information of the target store on the first page to recommend the target store to the user. The first page is a store recommendation results page, including media-based store information of at least one target store.

[0035] It should be noted here that, Figure 1 In the application scenario shown, the store information recommendation process is completed by the cooperation of terminal device 11a and server device 11b, but it is not limited to this. The above-mentioned store information recommendation process can be implemented independently by terminal device 11a. When terminal device 11a implements the process independently, the actions that were originally performed by server device 11b are all performed by terminal device 11a. For a detailed description of the store information recommendation process, please refer to the following method embodiments.

[0036] Figure 2a This is a flowchart illustrating a store information recommendation method provided in an embodiment of this application. The store information recommendation method provided in this embodiment can be implemented by a terminal device alone, or it can be completed by the terminal device and a server device working together. Figure 2a As shown, the method includes:

[0037] 201. Respond to the trigger operation of store recommendations and obtain user behavior data and / or store sales data of at least one store within a specified time period;

[0038] 202. Based on user behavior data and / or sales data of at least one store within a specified time period, identify the target store for the associated media event from at least one store.

[0039] 203、generate the media shop information of the target shop according to the media event associated with the target shop, the media shop information comprising information associated with the media event;

[0040] 204、display the media shop information of the target shop on the first page to recommend the target shop to the user.

[0041] In this embodiment, when the user needs the e-commerce APP to recommend a shop during the use of the e-commerce APP installed on the terminal device, the user can initiate a trigger operation of shop recommendation to activate the shop recommendation function of the e-commerce APP. The way in which the user initiates the trigger operation of shop recommendation is not limited, for example, a shop recommendation function entry is set on a specific page, for example, a "daily good shop" function entry is set on the home page, but not limited to, the user can initiate the trigger operation of shop recommendation through the shop recommendation function entry on the specific page; for example, in the case that the e-commerce APP supports voice recognition function, the user can also initiate the trigger operation of shop recommendation through voice instruction, for example, the trigger operation of shop recommendation can be initiated through, but not limited to, the voice information of "shop recommendation".

[0042] In this embodiment, when the user initiates the trigger operation of shop recommendation, the terminal device can execute the shop recommendation function of the e-commerce APP to recommend shops to the user. Specifically, the terminal device can obtain the heat representation data of at least one shop in a specified period in response to the trigger operation of shop recommendation. The at least one shop forms an initial shop set for shop recommendation in this embodiment, which can be all shops provided by the e-commerce APP, or part of the shops, which is not limited. In the case that the initial shop set is part of the shops provided by the e-commerce APP, the initial shop set required for shop recommendation can be flexibly selected according to application requirements. The way of selecting part of the shops to form the initial shop set is exemplified, including but not limited to any of the following ways or a combination of at least two of the following ways:

[0043] a1: shops in normal business state when the user initiates the shop recommendation operation can be selected, and shops that are suspended or closed are not concerned.

[0044] a2: according to the current location of the user, shops whose service range can cover the current location of the user can be selected, and shops whose service range cannot cover the current location of the user are not concerned.

[0045] a3: according to the user's commodity demand information, shops that can provide the user with the required commodity information can be selected, and shops that cannot provide the user with the required commodity information are not concerned. The user's commodity demand information can be determined according to the user's portrait data and / or network behavior data in a certain period.

[0046] Mode a4: According to the current location of the user, the store in the normal operating state when the user initiates the store recommendation operation can be selected from the store whose service range can cover the current location of the user. The store that is temporarily suspended or closed and the store whose service range cannot cover the current location of the user is not concerned.

[0047] Mode a5: According to the current location of the user and the commodity demand information, the store in the normal operating state when the user initiates the store recommendation operation can be selected from the store whose service range can cover the current location of the user and can provide the user with the required commodity information. The store that is temporarily suspended or closed, the store whose service range cannot cover the current location of the user, and the store that cannot provide the user with the required commodity information is not concerned.

[0048] Mode a6: According to the attribute information of each store, the store without the first specific attribute can be selected. The store with the first specific attribute is not concerned. For example, the first specific attribute can be a lower praise rate, or a sports brand, or a store attribute such as no recent new commodity information.

[0049] Mode a7: According to the attribute information of each store, the store with the second specific attribute can be selected. The store without the second specific attribute is not concerned. For example, the second specific attribute can be a specific operating category, such as women's clothing or children's clothing, or a store attribute such as operating time greater than 10 years, or more than 20,000 return customers.

[0050] In the embodiment, the heat representation data of each store can include, but is not limited to, user behavior data and / or store sales data of each store in a specified period. The specified period can be flexibly set according to application requirements, and preferably can be a recent period, for example, a recent week, a recent ten days, a recent month or a recent three months, etc. For any store, the user behavior data includes various behavior data generated by each user accessing the store in the specified period, including but not limited to various behavior data such as store access, product browsing, adding to the shopping cart, ordering, payment, comments, and consultation, etc. The behavior data includes user information initiating the behavior data, the type of behavior data, the time when the behavior data occurs, and the object involved in the behavior data (such as store, product information or payment amount), etc. Through the statistics of the user behavior data, for example, how many users initiate the access operation to the store in the specified period can be counted, and how many users perform browsing operation, adding to the shopping cart operation, ordering operation or payment operation in the store in the specified period can also be counted. Through the statistical information, the access heat information of the store can be obtained. Further, the statistics of which product information in the store is browsed by the user in the specified period and the number of times the product information is browsed, which product information is added to the shopping cart by the user and the number of product information added to the shopping cart, which product information is ordered by the user and the number of times the product information is ordered, which product information is paid by the user and the number of times the product information is paid, etc. can be counted. Through the statistical information, the access heat information of each product information in the store can be obtained. For any store, the store sales data includes the sales volume, sales amount and order quantity of each statistical dimension generated by the store in the specified period. The store sales data can also reflect the access heat information of the store in the specified period. The greater the sales volume, sales amount or order quantity, the more the number of users accessing the store, the number of users performing ordering, payment and other operations on the product information in the store, which means that the access heat of the store is higher.

[0051] In the embodiment, when recommending the store, the user behavior data of the store in the specified period can be used alone, which can reflect the access heat information of the store in the specified period. Alternatively, the store sales data of the store in the specified period can be used alone, which can reflect the access heat information of the store in the specified period. Alternatively, the user behavior data and the store sales data of the store in the specified period can be used simultaneously.

[0052] After obtaining the user behavior data and / or the store sales data of the at least one store in the specified period, a store associated with a media event can be obtained from the at least one store according to the user behavior data and / or the store sales data of the at least one store in the specified period. For ease of description and differentiation, the store associated with the media event is referred to as a target store. The known media event includes at least one media event obtained. A media event refers to an event with a certain degree of heat that is spread to the public through mass media or the network, for example, an entertainment event, a news event, a social event, etc. Each media event has its own description information, which is used to describe the content and attributes of the media event. Alternatively, various media events and their description information can be crawled from the network through a network crawler, or can be registered in advance with a social platform or a media platform that pushes various media events, and the social platform or the media platform pushes various media events and their description information. The description information of the media event includes attribute information of the media event, a title of the media event, text content, audio information, and / or video information.

[0053] In the embodiments of the present application, when the target store is obtained, at least one candidate store can be selected from the at least one store according to the user behavior data and / or the store sales data of the at least one store in the specified period; then, the at least one candidate store is associated with the known media event, and then the target store associated with the media event is obtained. Further, the visit heat information of the at least one store can be generated according to the user behavior data and / or the store sales data of the at least one store in the specified period; and at least one candidate store satisfying a heat condition can be selected from the at least one store according to the visit heat information of the at least one store.

[0054] For example, the user behavior data and / or the store sales data of the store in the specified period can be counted to obtain numerical data such as the total number of visits, the total number of orders, the total number of views, the total sales, the total sales volume, etc. of the store, and then the numerical data is normalized, and the normalized data is used as the visit heat information of the store; or the numerical data can be directly used as the visit heat information of the store; or the numerical data can be weighted and summed, and the result of the weighted sum is used as the visit heat information of the store. Then, according to the visit heat information of the at least one store, at least one store with the maximum visit heat can be selected as a candidate store according to the set number of candidate stores; or a store with visit heat information greater than a set visit heat threshold can be selected as a candidate store according to the visit heat information of the at least one store.

[0055] Further optionally, when selecting at least one candidate store from the at least one store according to the visit heat information of the at least one store, in addition to considering the visit heat information of the store, other attribute information of the store, such as the type of the store, the main category, the business years, the praise rate, etc., can be combined to comprehensively consider the multi-dimensional store attributes including the visit heat information, for example, to perform weighted summation on the multi-dimensional store attributes to obtain a comprehensive quality score of the store, and to select at least one store with the highest comprehensive quality score as the candidate store.

[0056] After the candidate store is selected, the at least one candidate store can be associated with the known media event to obtain the target store associated with the media event. Specifically, when the at least one candidate store is associated with the known media event, the at least one candidate store can be associated with the known media event from at least one information dimension. Wherein, the at least one information dimension is mainly from the perspective of the candidate store, and the at least one dimension information of the candidate store is associated with the known media event. For any candidate store, it is possible to successfully associate with the media event, or it is impossible to associate with any media event. Optionally, the candidate store associated with the media event can be used as the target store, or the candidate store associated with the media event and meeting other screening conditions can be used as the target store. Wherein, the other screening conditions can be, but are not limited to, the type of the store, the size of the store, etc. For the same target store, it can be associated with one media event, or it can be associated with multiple media events at the same time; for different target stores, it can be associated with the same media event, or it can be associated with different media events.

[0057] Further optionally, the at least one candidate store is associated with the known media event from at least one information dimension, including but not limited to the following implementation manners:

[0058] Manner b1: for any candidate store, the information of at least one dimension of the candidate store is respectively matched with the description information of each known media event, and if the description information of the known media event is matched, the candidate store is used as the target store associated with the matched known media event.

[0059] Manner b2: target attribute words are extracted from the description information of the known media event, the target attribute words include store attribute words and / or commodity attribute words; for any candidate store, the information of at least one dimension of the candidate store is matched with the target attribute words; if the target attribute words are matched, the candidate store is used as the target store associated with the known media event corresponding to the target attribute words.

[0060] In the manner b1 and the manner b2, the information of at least one dimension of the candidate store includes, but is not limited to, attribute information of the candidate store and / or commodity information in the candidate store. The attribute information of the candidate store belongs to one dimension of information, and the commodity information in the candidate store belongs to another dimension of information. In addition, the attribute information of the candidate store includes multiple attribute information such as type, main category, business duration, and heat; and the commodity information in the candidate store includes information such as pictures of each commodity, commodity description information (for example, commodity name, price, specification, and other detail information), and comments.

[0061] In the manner b1, the attribute information of the candidate store and / or the commodity information in the candidate store is directly matched with the description information of the known media event. Optionally, a specific matching manner includes: extracting keywords from the attribute information of the candidate store and / or the commodity information in the candidate store to obtain a keyword set; performing word segmentation on the description information of the known media event to obtain a word segmentation set; matching the keywords in the keyword set with the word segments in the word segmentation set two by two, and then counting the probability in the matching, to determine whether the candidate store is associated with the known media event according to the probability in the matching. For example, if the probability in the matching is greater than a set probability threshold, it is determined that the candidate store is associated with the known media event; otherwise, if the probability in the matching is less than or equal to the set probability threshold, it is determined that the candidate store cannot be associated with the known media event.

[0062] In the manner b2, target attribute words, i.e., store attribute words and / or commodity attribute words, are first extracted from the description information of the known media event; and then, the attribute information of the candidate store and / or the commodity information in the candidate store is matched with the target attribute words. The commodity attribute word refers to a word appearing in the description information of the known media event and capable of reflecting specific commodity information to a certain extent, which can be, but is not limited to, a commodity name, a model, a category, a manufacturer, a promotional phrase, and the like appearing in the description information of the media event. The store attribute word refers to a word appearing in the description information of the known media event and capable of reflecting specific store information to a certain extent, which can be, but is not limited to, a store name, a main category, a nickname, a promotional phrase, and the like appearing in the description information of the media event.

[0063] Optionally, in the manner b2, an embodiment of extracting target attribute words from the description information of the known media event includes: identifying attribute information and content information of the known media event from the description information of the known media event, and extracting target attribute words from the attribute information and the content information respectively. Further, in the case that the attribute information or the content information contains picture, audio and / or video information, the picture, audio and / or video information in the attribute information or the content information is converted into text information respectively, the converted text information and the text information originally contained in the attribute information and the content information are segmented, the segmented text information is identified by part of speech to obtain nouns or noun phrases, and the nouns or noun phrases are identified by word meaning to obtain the store attribute words and / or the commodity attribute words.

[0064] Optionally, in the manner b2, a manner of matching the attribute information of the candidate store and / or the commodity information in the candidate store with the target attribute words includes:

[0065] One is a manner of matching the attribute information of the candidate store with the target attribute words, specifically: in the case that the attribute information of the candidate store contains picture, audio and / or video information, the picture, audio and / or video information is converted into text information, the converted text information and the text information originally contained in the attribute information of the candidate store are segmented, the selected nouns or noun phrases are matched with the target attribute words respectively, and the matching degree of the attribute information of the candidate store and the target attribute words is determined according to the number of matches; if the matching degree is greater than a set first matching degree threshold, it is determined that the candidate store is associated with the media event corresponding to the target attribute words; otherwise, if the matching degree is less than or equal to the set first matching degree threshold, it is determined that the candidate store is not associated with the media event corresponding to the target attribute words.

[0066] Another way of matching the commodity information in the candidate store with the target attribute word is as follows: for each commodity information in the candidate store, if the commodity information contains picture, audio and / or video information, the picture, audio and / or video information is converted into text information, the converted text information and the text information originally contained in the commodity information are segmented, and the selected nouns or noun phrases are matched with the target attribute word, and the matching degree of the commodity information and the target attribute word is determined according to the number of matches; if the matching degree is greater than a second matching degree threshold, it is determined that the commodity information is associated with the media event corresponding to the target attribute word; otherwise, if the matching degree is less than or equal to the second matching degree threshold, it is determined that the commodity information is not associated with the media event corresponding to the target attribute word. If there is commodity information associated with the media event corresponding to the target attribute word in the candidate store, it is determined that the candidate store is associated with the media event corresponding to the target attribute word; otherwise, it is determined that the candidate store is not associated with the media event corresponding to the target attribute word. Alternatively, if there is commodity information associated with the media event corresponding to the target attribute word in the candidate store and the number of commodity information associated with the media event is greater than a set number threshold, it is determined that the candidate store is associated with the media event; otherwise, it is determined that the candidate store is not associated with the media event corresponding to the target attribute word.

[0067] Another way of matching the commodity information in the candidate store with the target attribute word is as follows: for each commodity information in the candidate store, if the commodity information contains picture, audio and / or video information, the picture, audio and / or video information is converted into text information, the converted text information and the text information originally contained in the commodity information are segmented, and the selected nouns or noun phrases are matched with the target attribute word, and the matching degree of the commodity information and the target attribute word is determined according to the number of matches; if the matching degree is greater than a second matching degree threshold, it is determined that the commodity information is associated with the media event corresponding to the target attribute word; otherwise, if the matching degree is less than or equal to the second matching degree threshold, it is determined that the commodity information is not associated with the media event corresponding to the target attribute word. If there is commodity information associated with the media event corresponding to the target attribute word in the candidate store, it is determined that the candidate store is associated with the media event corresponding to the target attribute word; otherwise, it is determined that the candidate store is not associated with the media event corresponding to the target attribute word. Alternatively, if there is commodity information associated with the media event corresponding to the target attribute word in the candidate store and the number of commodity information associated with the media event is greater than a set number threshold, it is determined that the candidate store is associated with the media event; otherwise, it is determined that the candidate store is not associated with the media event corresponding to the target attribute word.

[0068] After the target store associated with the media event is acquired, the media store information of the target store can be generated according to the media event associated with the target store. The media store information refers to new store information generated by combining the media event and the traditional store information. The traditional store information only includes information related to the store itself, such as but not limited to: store name, store icon or avatar, store praise rate, store operating period, etc. Compared with the traditional store information, the media store information not only contains the traditional store information, but also includes information related to the media event, which attracts the attention of users to the store through the media event. Then, the media store information of the target store is displayed on the first page to achieve the purpose of recommending the target store to the user.

[0069] In this embodiment, the way of generating the media store information of the target store according to the media event associated with the target store is not limited, and the type and quantity of information related to the media event contained in the media store information are also not limited. The way of generating the media store information is illustrated as follows:

[0070] Method c1: According to the association degree of each commodity information in the target store and the media event, at least one commodity information with an association degree meeting the requirements is selected, and commodity text information of the at least one commodity information is generated according to the description information of the media event as the media store information.

[0071] Method c2: According to the attribute information of the target store and the description information of the media event, store text information associated with the media event is generated as the media store information.

[0072] Method c3: According to the heat information of each commodity information in the target store, at least one commodity information with heat information meeting the requirements is selected, and commodity text information of the at least one commodity information is generated according to the description information of the media event as the media store information.

[0073] In method c1, product information and media events are integrated to form media-based store information. Optionally, based on the descriptions of each product information item and media event in the target store, the correlation between each product information item and the media event can be analyzed, as well as the degree of correlation when product information and media events are correlated. Then, from the product information items associated with the media event, at least one product information item with a correlation degree that meets the requirements can be selected. For example, at least one product information item with the highest correlation degree can be selected, and the number of product information items to be selected can be pre-specified or set. Alternatively, at least one product information item with a correlation degree greater than a set correlation degree threshold can be selected, and the correlation degree threshold can be pre-set. Specifically, when analyzing whether each product information item is correlated with the media event, matching can be performed based on the target attribute words corresponding to each product information item and the media event. The correlation between product information and media event is determined based on whether the matching degree is greater than a set second matching degree threshold. The detailed process of this method can be found in the description of method b2 above, and will not be repeated here.

[0074] After selecting at least one product information item that meets the relevance requirements, product copy information for at least one product item can be generated based on the description information of the media event. This product copy information is obtained by integrating it with the media event and differs from traditional product description information. For example, traditional product description information may include product images and prices, while product copy information integrated with media events may include product images, prices, and information related to the media event, such as "This product became a bestseller because of media event xxx," "This product is the same product featured in media event xxx," or "This product became a celebrity favorite because of media event xxx," etc. Figure 2b - Figure 2d As shown. It should be noted that "information related to media events" is merely illustrative and not limited to this; any information format or style related to media events is applicable to the embodiments of this application. It should also be noted that the media-enabled store information of the target store includes some traditional store information, such as store name and customer satisfaction rating.

[0075] In the manner c2, the store dimension is fused with the media event to form the media store information. Optionally, the attribute information of the target store and the description information of the media event can be fused by using a preset first text template to generate the store text information associated with the media event. Optionally, the first text template can be a cause-effect type text template, which includes a reason area and a result area. The reason area includes the information of the media event to be filled and the preset reason text, and the result area includes the information of the target store to be filled and the preset result text. For example, the preset reason text can be "because of the driving of xxx", where xxx is the information of the media event to be filled; and the preset result text can be "xxx is a hit", where xxx is the information of the target store to be filled. Alternatively, the first text template can be an association type text template, which includes a first area, a second area and an association word between the two areas. The first area and the second area are to-be-filled areas, and are used to fill the information of the media event and the information of the target store, respectively. The filling positions of the two information are not limited, and the information of the media event can be filled in the first area and the information of the target store can be filled in the second area, or vice versa. Optionally, an example of the association type text template is, for example, "xxx is associated with xxx", "xxx has appeared in xxx", "xxx is a store in xxx", etc.

[0076] In the manner c3, the store dimension is fused with the media event to form the media store information. Optionally, in the case where the target store is associated with the media event, at least one commodity information with the required heat information can be selected from the target store according to the heat information of each commodity information in the target store, regardless of whether the commodity information in the target store is associated with the media event. Then, the store dimension is fused with the media event to form the media store information, that is, the commodity text information of at least one commodity information is generated according to the description information of the media event. The heat information of each commodity information can be selected from the user behavior data and / or store sales data of the target store in a specified period, and the user behavior data and / or store sales data corresponding to the commodity information is analyzed to obtain the heat information of the commodity information.

[0077] Further optionally, in the above manner c1 and manner c3, after the at least one commodity information is selected, the commodity information of the at least one commodity information can be generated according to the description information of the media event. One manner of generating the commodity information of the at least one commodity information includes: using a preset second text template to perform text translation on the user behavior data and / or the store sales data corresponding to the at least one commodity information, to obtain the heat text information corresponding to the at least one commodity information; and supplementing the heat text information corresponding to the at least one commodity information with the description information of the media event as the heat reason information, to obtain the commodity information of the at least one commodity information. In this embodiment, the second text template is used to perform text translation on the user behavior data and / or the store sales data corresponding to each commodity information, for example, the user behavior data and / or the store sales data corresponding to the commodity information can be counted as the access amount and / or the sales amount (or the transaction amount) of the commodity information, and for the commodity information whose access amount exceeds an access amount threshold and / or whose sales amount exceeds a sales amount threshold, the user behavior data and / or the store sales data are translated into text information such as “the xxx commodity information is very popular” or “the xxx commodity information is very popular”.

[0078] Next, the description information of the media event is supplemented as the heat reason information to the heat text information corresponding to the at least one commodity information, to obtain the commodity information of the at least one commodity information. Optionally, the description information of the media event can be directly supplemented as the heat reason information before the heat text information corresponding to the commodity information, to obtain the commodity information of the commodity information which contains the heat reason information and the heat text information. Alternatively, the description information of the media event can be supplemented as the reason area by referring to the above first text template, corresponding to the result area of the heat text information corresponding to the at least one commodity information, and the first text template is filled with information, to obtain the commodity information of the at least one commodity information.

[0079] In an optional embodiment, considering that the number of media events occurring in a period of time can be large, accordingly, the number of target stores associated with the media events can also be large, in order to recommend higher-quality target stores to the user, the target stores can be filtered or screened. Specifically, when the number of target stores is greater than a set number threshold, the multiple target stores can be filtered according to the attribute information of the media events associated with the target stores, the commodity preference information of the user, and / or the attribute information of the target stores, to reduce the number of target stores, so that the user can more quickly and conveniently find the interested store from the target stores with an appropriate number and access the store.

[0080] In this embodiment, the specific implementation method for filtering multiple target stores based on the attribute information of media events associated with the target store, the user's product preference information, and / or the attribute information of the target store is not limited. Any filtering method that can reduce the number of target stores is applicable to the embodiments of this application. Examples of filtering methods are given below:

[0081] Method d1: Filter multiple target stores based on the attribute information of the media events associated with the target store.

[0082] Method d2: Filter multiple target stores based on the user's product preference information.

[0083] Method d3: Filter multiple target stores based on their attribute information.

[0084] Method d4: Filter multiple target stores based on the attribute information of media events associated with the target store and the user's product preference information.

[0085] Method d5: Filter multiple target stores based on the attribute information of the media events associated with the target store and the attribute information of the target store.

[0086] Method d6: Filter multiple target stores based on the target store's attribute information and the user's product preference information.

[0087] Method d7: Filter multiple target stores based on the attribute information of media events associated with the target store, the user's product preference information, and the attribute information of the target store.

[0088] In the above methods, when filtering multiple target stores based on the attribute information of the media events associated with the target store, the target stores with lower media event popularity information can be filtered out based on the popularity information of the associated media events. For example, target stores whose media event popularity information is less than a set popularity threshold can be filtered out, or the target stores can be sorted in descending order of the popularity information of the associated media events, and the last few target stores in the ranking can be filtered out.

[0089] In the above methods, when filtering multiple target stores based on the attribute information of the target stores, the target stores with lower popularity information can be filtered out based on the popularity information of the target stores. For example, target stores with popularity information less than the set popularity threshold can be filtered out, or the target stores can be sorted in descending order of popularity information and the last few target stores in the ranking can be filtered out.

[0090] In the above manners, when filtering the plurality of target stores according to the commodity preference information of the user, the commodity information or commodity category preferred by the user can be determined according to the commodity preference information of the user, and the preference degree of the user to each target store can be calculated according to the commodity information or commodity category preferred by the user in combination with the attribute information of each target store; the target stores with lower preference degrees are filtered out, for example, the target stores with a preference degree less than a set preference degree threshold are filtered out, or the target stores are sorted in order of preference degree from high to low, and the last several target stores in the ranking are filtered out.

[0091] After generating the media store information of the target store, the media store information of the target store can be displayed on the first page to achieve the purpose of recommending the target store to the user. The first page is a store recommendation result page. In this embodiment, the implementation form and page layout of the first page are not limited, and any page form and layout that can display the media store information of the target store to the user are suitable for this embodiment.

[0092] In an optional embodiment, the media store information of the target store can be displayed on the first page, and the first page includes a plurality of display areas, each display area carrying the media information of one target store. As shown in Figure 2b , another page layout is as shown in Figure 2c . In Figure 2b , a streaming layout is adopted, and the media store information of each target store is sequentially displayed in the form of a card on the first page; in Figure 2c , a multi-column layout is adopted, specifically including two columns, and the media store information of each target store is displayed in the form of a card in two columns on the first page.

[0093] In an optional embodiment, in order to facilitate the user to quickly select the required store from the target stores for access, the target stores can be classified and displayed. Specifically, classification labels can be set in advance, and each classification label corresponds to a type of store, wherein the classification labels are not limited and can be flexibly set according to application requirements. Based on the pre-set classification labels and the attribute information of the target stores, the target stores are classified to obtain at least one type of target stores; then, at least one type of target stores is classified and displayed according to the classification result. Further optionally, at least one tab page can be embedded in the first page, each tab page corresponds to a classification label, and is used to display the store information corresponding to the classification label. Based on this, at least one type of target stores can be respectively displayed on at least one tab page embedded in the first page. As shown in Figure 2d , it is an interface schematic diagram of the first page including a plurality of tab pages. In Figure 2dThe table shows N tabs, where tabs 1 and 2 correspond to women's clothing and children's clothing, respectively, and tab N corresponds to kitchenware. The current display shows the target store and its media store information in tab 1.

[0094] Optionally, to further facilitate users in quickly selecting the desired stores from each category of target stores, before displaying each category of target stores on the corresponding tab, at least one category of target stores can be sorted according to the user's product preference information, the attribute information of the media events associated with the target stores, and / or the attribute information of the target stores themselves. Then, according to the sorting results of at least one category of target stores, at least one category of target stores is displayed on at least one tab embedded in the first page. For example, target stores with higher user preference can be ranked first for priority display; target stores associated with more popular media events can be ranked first for priority display; and / or target stores with specific attributes (e.g., higher popularity) can be ranked first for priority display.

[0095] Furthermore, such as Figure 2b - Figure 2d The first page also includes a first redirect control. This first redirect control can be text, an image, an icon, or a button, etc., and is not limited thereto. The first redirect control points to a second page, which is a page that recommends stores in an aggregated manner, and can be simply referred to as the store aggregation page. Specifically, when a user wants to view the stores on the store aggregation page, they can initiate an access operation through the first redirect control. Based on this, as... Figure 2e As shown, the method of this embodiment, after step 204, further includes:

[0096] 205. Responding to the triggering operation of the first jump control, jump from the first page to the second page. The second page displays multiple store information aggregated according to the first aggregation dimension, as well as a second jump control associated with the second aggregation dimension; wherein, the second jump control points to the third page, and the third page includes multiple store information aggregated according to the second aggregation dimension.

[0097] Further optional, such as Figure 2e As shown, after step 205, the following steps are also included:

[0098] 206. In response to the triggering operation of the second jump control, jump from the second page to the third page, where multiple store information aggregated according to the second aggregation dimension is displayed.

[0099] In this embodiment, the aggregation dimension for displaying stores is not limited. Displaying stores in aggregate means grouping stores with the same aggregation dimension together and displaying them on the same page.

[0100] In one optional embodiment, the first aggregation dimension and the second aggregation dimension can be of the same type, but they are different aggregation dimensions. In one scenario, stores can be aggregated by physical blocks, and the first aggregation dimension and the second aggregation dimension can be different physical blocks. Preferably, the physical block corresponding to the first aggregation dimension can be determined based on the user's current location, for example, it can be the physical block closest to the user's current location. Then, the store information of stores associated with this physical block is aggregated and displayed on the second page. The stores associated with this physical block can be, for example, physical stores located in this physical block, or stores located in this physical block. The physical block corresponding to the second aggregation dimension can be other well-known physical blocks or physical blocks relatively far from the user's current location.

[0101] In one optional embodiment, the first aggregation dimension and the second aggregation dimension can be different types of aggregation dimensions. In one scenario, the first aggregation dimension can be a physical street block, and the second aggregation dimension can be a store style or main product category, etc.

[0102] In the above embodiments, the second aggregation dimension can be one or more. The second page or the third page has the same or similar page format; a second page or third page format is as follows: Figure 2f As shown. It should be noted that the multiple stores aggregated and displayed on the second or third page may include only stores associated with the media event, only stores not associated with the media event, or both; there is no limitation in this regard. Figure 2f The illustration uses both stores associated with and not associated with media events. Target store 1 is associated with a media event, and target store M is not associated with a media event. Furthermore, to enhance the store display, 3D or AR technologies can be used to showcase the stores, increasing the immersive shopping experience.

[0103] In this embodiment, integrating media events into the store recommendation process enriches the recommendations by showcasing more stores related to those events to users. Furthermore, displaying media-style store information increases the store's appeal, raising the probability of user visits and improving the efficiency of obtaining desired products, thus enhancing the user experience of the e-commerce application. Moreover, it increases store exposure and user traffic, ultimately boosting sales figures.

[0104] It should be noted here that, in the above Figure 2aThe illustrated embodiments can be implemented locally on the terminal device alone, or they can be implemented in conjunction with the terminal device and the server device. In the above... Figure 2a In the embodiment shown, implemented by a terminal device and a server device, the method for recommending store information is described from the perspective of the terminal device. The method includes: the terminal device responding to a trigger operation for store recommendation by sending a store recommendation request to the server device; receiving media-formatted information of a target store returned by the server device, wherein the target store is a store associated with a media event, determined by the server device based on user behavior data and / or sales data of at least one store within a specified time period, and the media-formatted store information is generated based on the media event associated with the target store; and displaying the media-formatted store information of the target store on a first page to recommend the target store to the user.

[0105] From the perspective of the server-side device, a store information recommendation method includes: responding to a store recommendation request sent by a terminal device, obtaining user behavior data and / or store sales data of at least one store within a specified time period; based on the user behavior data and / or store sales data of at least one store within the specified time period, obtaining a target store associated with a media event from the at least one store; generating media-formatted store information of the target store based on the media event associated with the target store, the media-formatted store information including information associated with the media event; and sending the media-formatted store information of the target store to the terminal device for the terminal device to display the media-formatted store information of the target store. Detailed descriptions of the related operations can be found in the above embodiments and will not be repeated here.

[0106] In addition to the embodiments described above, this application also provides a method for recommending store information, in which media events are integrated into the store recommendation process from different dimensions. Specifically, as shown in the example... Figure 3 As shown, the store information recommendation method includes:

[0107] 301. Obtain target media events that occur within a specified time period;

[0108] 302. Identify target stores that are associated with the target media event from at least one store;

[0109] 303. Based on the target media event, generate media-based store information for the target store, wherein the media-based store information includes information associated with the target media event;

[0110] 304. Display media-based store information of the target store on the first page to recommend the target store to users.

[0111] In the embodiment, the target media event is acquired first from the perspective of a media event, and then the target store associated with the target media event is determined; after the target store associated with the target media event is determined, the media store information of the target store can be generated according to the target media event, and the media store information of the target store is displayed on the first page to achieve the purpose of recommending the target store to the user. For the acquisition method of the media event, refer to the foregoing embodiments, which will not be described here again.

[0112] In an optional embodiment, at least one media event occurring in a specified period can be acquired, and a media event with a heat greater than a first set heat threshold and containing a target attribute word is selected as a target media event from the at least one media event; the target attribute word includes a store attribute word and / or a commodity attribute word.

[0113] In an optional embodiment, the target store associated with the target media event is determined from at least one store, including: extracting a target attribute word from the description information of the target media event, the target attribute word including a store attribute word and / or a commodity attribute word; matching the attribute information of any store and / or the commodity information in the any store with the target attribute word; and selecting a store matching the target attribute word as a candidate store, and selecting a target store from the candidate store. For the detailed implementation of extracting the target attribute word from the description information of the target media event and matching the attribute information of any store and / or the commodity information in the any store with the target attribute word, refer to the foregoing embodiments, which will not be described here again.

[0114] After the candidate store is selected, the target store can be selected from the candidate store. Alternatively, at least one store can be randomly selected from the candidate store as the target store, or at least one store with a higher association degree can be selected from the candidate store as the target store according to the association degree of the candidate store with the target media event; or the target store can be selected from at least one candidate store according to the attribute information of the candidate store and / or the commodity preference information of the user.

[0115] For the detailed implementation of generating the media store information of the target store according to the target media event and displaying the media store information of the target store on the first page, refer to the foregoing embodiments, which will not be described here again.

[0116] Herein, Figure 3 The store information recommendation method shown can be implemented by the terminal device and the server device in cooperation, or can be implemented by the terminal device alone.

[0117] In addition to the foregoing embodiments, the embodiments of the present application also provide a store information recommendation method, as shown in Figure 4 The store information recommendation method includes:

[0118] 401、in response to a triggering operation of the store recommendation, obtaining a current location of the user;

[0119] 402、determining a first physical block according to the current location of the user;

[0120] 403、obtaining target stores associated with the first physical block;

[0121] 404、displaying store information of the target stores associated with the first physical block on a first page.

[0122] In the embodiment, the store recommendation can be made to the user in a store aggregation manner according to the current location of the user. Specifically, the stores are aggregated in a physical block as an aggregation dimension, that is, a first physical block is determined according to the current location of the user, and then target stores associated with the first physical block are displayed on a first page to display store information of the target stores associated with the first physical block, so as to achieve the purpose of recommending stores to the user in a store aggregation manner. The first physical block can be the nearest physical block to the current location of the user, but is not limited thereto. In the embodiments of the present application, the definition of the physical block is not limited, and can be an arbitrary physical block, or some well-known commercial blocks or tourist blocks, or blocks where shopping malls or supermarkets are located, etc. The stores associated with the first physical block can be online stores having physical stores or joint stores in the first physical block, or online stores having pickup points or after-sales service stations in the first physical block.

[0123] In an optional embodiment, the first page further includes at least one block switching control, and different block switching controls correspond to different other physical blocks. The method further includes: in response to a triggering operation of any block switching control, jumping from the first page to a second page, and the second page includes store information of target stores associated with the other physical block corresponding to the any block switching control.

[0124] In an optional embodiment, the above-mentioned one embodiment of obtaining the target stores associated with the first physical block includes: obtaining at least one store associated with the first physical block according to block attribute information of each online store; and obtaining a target store associated with a media event from the at least one store according to user behavior data and / or store sales data of the at least one store in a specified period. For detailed embodiments of obtaining a target store associated with a media event from the at least one store according to user behavior data and / or store sales data of the at least one store in a specified period, refer to the foregoing embodiments, which will not be described herein.

[0125] In the embodiment, the shops are aggregated according to the current location of the user and the physical block, and then the shops close to the user and associated with the same physical block are aggregated and recommended to the user, so as to combine the online shop and the offline physical shop, and provide more convenient and comprehensive services for the user. For example, the user can place an order in the online shop, and then pick up the goods in the physical shop, or the physical shop can complete the delivery nearby, or the user can try on clothes or makeup or after-sales service in the physical shop, and in addition, the user can also handle other matters in the offline physical shop.

[0126] It should be noted that the execution subject of each step of the method provided in the above embodiments can be the same device, or the method can also be executed by different devices as the execution subject. For example, the execution subject of steps 201 to 204 can be device A; for another example, the execution subject of steps 201 and 204 can be device A, and the execution subject of steps 202 and 203 can be device B; and the like.

[0127] In addition, in some of the processes described in the above embodiments and the accompanying drawings, a plurality of operations appearing in a specific order are included, but it should be clear that these operations can be executed or executed in parallel without the order in which they appear in this text. The serial numbers of the operations, such as 401, 402, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes can include more or fewer operations, and these operations can be executed in sequence or in parallel. It should be noted that the "first", "second", etc. described herein are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence. Also, "first" and "second" are not of different types.

[0128] Figure 5a A structural schematic diagram of a shop information recommendation device provided by an embodiment of the present application is shown in FIG. 5. As shown in the figure, the device includes: Figure 5a

[0129] The data acquisition module 51a is configured to acquire user behavior data and / or shop sales data of at least one shop in a specified period in response to a triggering operation of shop recommendation.

[0130] The shop acquisition module 52a is configured to acquire a target shop associated with a media event from at least one shop according to the user behavior data and / or shop sales data of the at least one shop in the specified period.

[0131] The information generation module 53a is configured to generate media shop information of the target shop according to the media event associated with the target shop, and the media shop information includes information associated with the media event.

[0132] ​The information display module 54a is configured to display the media store information of the target store on the first page to recommend the target store to the user.

[0133] In an optional embodiment, the store obtaining module 52a is specifically configured to: generate visit popularity information of the at least one store according to the user behavior data and / or the store sales data of the at least one store in a specified period; select at least one candidate store that meets a popularity condition from the at least one store according to the visit popularity information of the at least one store; and associate the at least one candidate store with the known media event from at least one information dimension to obtain the target store associated with the media event.

[0134] Further optionally, when obtaining the target store associated with the media event, the store obtaining module 52a is specifically configured to: extract a target attribute word from the description information of the known media event, the target attribute word including a store attribute word and / or a commodity attribute word; match, for any candidate store, attribute information of the any candidate store and / or commodity information in the any candidate store with the target attribute word; and if the target attribute word is matched, take the any candidate store as the target store associated with the media event.

[0135] In an optional embodiment, as shown in Figure 5a the store information recommendation apparatus further includes a store filtering module 55a configured to, if the number of the target stores is greater than a set number threshold, filter the target stores according to attribute information of the media events associated with the target stores, commodity preference information of the user, and / or attribute information of the target stores.

[0136] In an optional embodiment, when generating the media store information of the target store according to the media event associated with the target store, the information generating module 53a is specifically configured to perform at least one of the following operations:

[0137] select at least one commodity information that meets a requirement in terms of the association degree from the commodity information in the target store, generate commodity text information of the at least one commodity information as the media store information according to the description information of the media event;

[0138] generate store text information associated with the media event as the media store information according to the attribute information of the target store and the description information of the media event;

[0139] select at least one commodity information that meets a requirement in terms of the popularity information from the commodity information in the target store, generate commodity text information of the at least one commodity information as the media store information according to the description information of the media event.

[0140] Further optionally, the information generation module 53a, in generating the product script information of the at least one product information according to the description information of the media event, is specifically configured to: perform script translation on the user behavior data and / or the store sales data corresponding to the at least one product information by using a preset script template, to obtain the heat script information corresponding to the at least one product information; and supplement the heat script information corresponding to the at least one product information with the description information of the media event as the heat reason information, to obtain the product script information of the at least one product information.

[0141] In an optional embodiment, the information display module 54a is specifically configured to: classify the target stores according to the preset classification labels and the attribute information of the target stores, to obtain at least one type of target stores; sort the at least one type of target stores respectively according to the product preference information of the user, the attribute information of the media event associated with the target stores, and / or the attribute information of the target stores; and display the at least one type of target stores respectively on at least one tab page embedded in the first page according to the sorting results of the at least one type of target stores, where one tab page corresponds to one classification label.

[0142] In an optional embodiment, the first page further includes a first jump control, as shown in Figure 5a The store information recommendation apparatus further includes a page jump module 56a configured to jump from the first page to a second page in response to a triggering operation of the first jump control, the second page displaying a plurality of store information aggregated according to a first aggregation dimension, and a second jump control associated with a second aggregation dimension; and the second jump control points to a third page, and the third page includes a plurality of store information aggregated according to the second aggregation dimension.

[0143] Further optionally, the page jump module 56a is further configured to jump from the second page to the third page in response to a triggering operation of the second jump control, and the third page displays the plurality of store information aggregated according to the second aggregation dimension.

[0144] Figure 5a The apparatus shown in Figure 2a The implementation principle and technical effects of the method of the embodiments shown in Figure 5a The apparatus shown in the embodiments, where each module performs operations in a specific manner, has been described in detail in the embodiments related to the method, and will not be described in detail here.

[0145] Figure 5b Another store information recommendation apparatus provided by the embodiments of the present application is shown in the structural schematic diagram. Figure 5b The apparatus includes:

[0146] An event obtaining module 51b is configured to obtain a target media event occurring within a specified time period;

[0147] A store determining module 52b is configured to determine a target store associated with the target media event from at least one store;

[0148] An information generating module 53b is configured to generate media store information of the target store according to the target media event, the media store information including information associated with the target media event;

[0149] An information displaying module 54b is configured to display the media store information of the target store on a first page to recommend the target store to a user.

[0150] In an optional embodiment, the event obtaining module 51b is specifically configured to: select, from at least one media event occurring within a specified time period, a media event having a heat greater than a first set heat threshold and containing a target attribute word as the target media event; and the target attribute word includes a store attribute word and / or a commodity attribute word.

[0151] In an optional embodiment, the store determining module 52b is specifically configured to: extract a target attribute word from description information of the target media event, the target attribute word including a store attribute word and / or a commodity attribute word; match, for any store, attribute information of any store and / or commodity information in any store with the target attribute word; and select the target store from candidate stores in which the target attribute word is matched.

[0152] Figure 5b The apparatus shown can perform Figure 3 The method of the embodiments shown, the implementation principles and technical effects will not be repeated. For the Figure 5b The apparatus shown, the specific manner in which each module performs operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

[0153] Figure 5c Another structure diagram of a store information recommendation apparatus provided by the embodiments of the present application is shown. As shown in the figure, Figure 5c The apparatus shown includes:

[0154] A location obtaining module 51c is configured to obtain a current location of a user in response to a triggering operation of store recommendation;

[0155] A block determining module 52c is configured to determine a first physical block according to the current location of the user;

[0156] A store obtaining module 53c is configured to obtain a target store associated with the first physical block;

[0157] The information display module 54c is configured to display, on the first page, store information of the target store associated with the first physical block.

[0158] In an optional embodiment, the first page further includes at least one block switching control, and different block switching controls correspond to different other physical blocks. Figure 5c As shown in the figure, the device further includes a page jump module 55c configured to jump from the first page to a second page in response to a triggering operation on any block switching control, and the second page includes store information of the target store associated with the other physical block corresponding to any block switching control.

[0159] In an optional embodiment, the store obtaining module 53c is specifically configured to: obtain at least one store associated with the first physical block according to the block attribute information of each online store; and obtain the target store associated with the media event from the at least one store according to the user behavior data and / or store sales data of the at least one store within a specified period.

[0160] Figure 5c The device shown in the figure can perform Figure 4 The method of the embodiments shown in the figure will not be described again in terms of implementation principles and technical effects. For the Figure 5c The device shown in the figure, wherein the specific manner in which each module performs an operation has been described in detail in the embodiments of the method, and will not be described in detail here.

[0161] Figure 6 A structural schematic diagram of an electronic device is provided for the embodiments of the present application. As shown in the figure, Figure 6 The electronic device includes a memory 61 and a processor 62.

[0162] The memory 61 is configured to store computer programs and can be configured to store other various data to support operations on the electronic device. Examples of the data include instructions of any application program or method for operating on the electronic device, contact data, messages, pictures, videos, etc.

[0163] The processor 62 is coupled to the memory 61 and is configured to execute the computer programs in the memory 61, so as to: in response to a triggering operation of store recommendation, obtain user behavior data and / or store sales data of at least one store within a specified period; obtain a target store associated with a media event from the at least one store according to the user behavior data and / or store sales data of the at least one store within the specified period; generate media store information of the target store according to the media event associated with the target store, wherein the media store information includes information associated with the media event; and display the media store information of the target store on a first page to recommend the target store to a user.

[0164] In an optional embodiment, the processor 62, when obtaining the target store associated with the media event from the at least one store, is specifically configured to: generate visit popularity information of the at least one store according to user behavior data and / or store sales data of the at least one store in a specified period; select at least one candidate store satisfying a popularity condition from the at least one store according to the visit popularity information of the at least one store; and associate the at least one candidate store with the known media event from at least one information dimension to obtain the target store associated with the media event.

[0165] Further optionally, the processor 62, when obtaining the target store associated with the media event, is specifically configured to: extract target attribute words from the description information of the known media event, the target attribute words including store attribute words and / or commodity attribute words; match, for any candidate store, attribute information of the any candidate store and / or commodity information in the any candidate store with the target attribute words; and if the target attribute words are matched, take the any candidate store as the target store associated with the media event.

[0166] In an optional embodiment, the processor 62 is further configured to: when the number of the target stores is greater than a set number threshold, filter the target stores according to attribute information of the media events associated with the target stores, commodity preference information of the user, and / or attribute information of the target stores.

[0167] In an optional embodiment, the processor 62, when generating the media store information of the target store according to the media event associated with the target store, is specifically configured to perform at least one of the following operations:

[0168] select at least one commodity information satisfying a requirement in association degree from the commodity information in the target store according to the association degree of the commodity information in the target store with the media event, and generate commodity text information of the at least one commodity information according to the description information of the media event as the media store information;

[0169] generate store text information associated with the media event according to the attribute information of the target store and the description information of the media event as the media store information;

[0170] select at least one commodity information satisfying a requirement in popularity information from the commodity information in the target store according to the popularity information of the commodity information in the target store, and generate commodity text information of the at least one commodity information according to the description information of the media event as the media store information.

[0171] Further, the processor 62 is specifically configured to: perform text translation on the user behavior data and / or the store sales data corresponding to the at least one commodity information by using a preset text template, to obtain hotness text information corresponding to the at least one commodity information; and supplement the hotness text information corresponding to the at least one commodity information with the description information of the media event as hotness reason information, to obtain the commodity text information of the at least one commodity information.

[0172] In an optional embodiment, the processor 62 is specifically configured to: classify the target stores according to preset classification labels and attribute information of the target stores, to obtain at least one type of target stores; sort the at least one type of target stores respectively according to the commodity preference information of the user, attribute information of the media event associated with the target stores and / or the attribute information of the target stores; and display the at least one type of target stores respectively on at least one tab page embedded in the first page according to the sorting results of the at least one type of target stores, wherein one tab page corresponds to one classification label.

[0173] In an optional embodiment, the first page further includes a first jump control, and the processor 62 is further configured to: jump from the first page to a second page in response to a triggering operation of the first jump control, and the second page displays a plurality of store information aggregated according to a first aggregation dimension and a second jump control associated with a second aggregation dimension; wherein the second jump control points to a third page, and the third page includes a plurality of store information aggregated according to the second aggregation dimension.

[0174] Further, the processor 62 is further configured to: jump from the second page to the third page in response to a triggering operation of the second jump control, and the third page displays a plurality of store information aggregated according to the second aggregation dimension.

[0175] Further, as shown in Figure 6 the electronic device further includes a communication component 63, a display 64, a power supply component 65, an audio component 66 and other components. Figure 6 only some components are shown schematically, and it does not mean that the electronic device only includes Figure 6 the components shown. In addition, Figure 6 the components in the dashed box in the embodiment are optional components, not mandatory components, and the specific implementation depends on the product form of the electronic device. The electronic device of the embodiment can be implemented as a terminal device such as a desktop computer, a notebook computer, a smart phone or an IOT device, or a server device such as a conventional server, a cloud server or a server array. If the electronic device of the embodiment is implemented as a terminal device such as a desktop computer, a notebook computer or a smart phone, it can include Figure 6The components within the dashed box; if the electronic device in this embodiment is implemented as a conventional server, cloud server, or server array, it may be omitted. Figure 6 The component within the dashed box.

[0176] This application also provides an electronic device, the structure of which is similar to... Figure 6 The electronic devices shown have the same or similar structures; see details below. Figure 6 The structure of the electronic device shown is implemented in this embodiment, and the electronic device provided in this embodiment is similar to... Figure 6 The main difference between the electronic devices in the illustrated embodiments lies in the different functions implemented by the computer programs stored in the memory executed by the processor. For the electronic device provided in this embodiment, the processor executing the computer programs stored in the memory can be used to: respond to a triggering operation for store recommendations and send a store recommendation request to the server device; receive media-formatted information of the target store returned by the server device, wherein the target store is a store associated with a media event determined by the server device based on user behavior data and / or sales data of at least one store within a specified time period, and the media-formatted store information is generated based on the media event associated with the target store; and display the media-formatted store information of the target store on a first page to recommend the target store to the user.

[0177] This application also provides an electronic device, the structure of which is similar to... Figure 6 The electronic devices shown have the same or similar structures; see details below. Figure 6 The structure of the electronic device shown is implemented in this embodiment, and the electronic device provided in this embodiment is similar to... Figure 6 The main difference between the electronic devices in the illustrated embodiments lies in the different functions implemented by the computer programs stored in the memory executed by the processor. For the electronic device provided in this embodiment, the processor executing the computer programs stored in the memory can be used to: respond to a store recommendation request sent by a terminal device; obtain user behavior data and / or store sales data of at least one store within a specified time period; based on the user behavior data and / or store sales data of at least one store within the specified time period, obtain the target store associated with a media event from at least one store; generate media-enhanced store information for the target store based on the media events associated with the target store, the media-enhanced store information including information associated with the media events; and send the media-enhanced store information of the target store to the terminal device for the terminal device to display the media-enhanced store information of the target store.

[0178] The electronic device described in the above embodiments of this application can perform... Figure 2a The implementation principle and technical effects of the method in the illustrated embodiment will not be repeated here. The specific methods of the above-mentioned related operations have been described in detail in the embodiments of the method, and will not be elaborated here.

[0179] The embodiment of the present application also provides an electronic device, and the structure of the electronic device is the same or similar to the structure of the electronic device shown in Figure 6 The embodiment of the present application also provides an electronic device, and the structure of the electronic device is the same or similar to the structure of the electronic device shown in Figure 6 The embodiment of the present application also provides an electronic device, and the structure of the electronic device is the same or similar to the structure of the electronic device shown in Figure 6 The embodiment of the present application also provides an electronic device, and the structure of the electronic device is the same or similar to the structure of the electronic device shown in

[0180] In an optional embodiment, the processor is specifically configured to: select, as the target media event, a media event that has a heat greater than a first set heat threshold and contains a target attribute word from at least one media event occurring within a specified period; and the target attribute word includes a shop attribute word and / or a commodity attribute word.

[0181] In an optional embodiment, the processor is specifically configured to: extract the target attribute word from the description information of the target media event, the target attribute word including a shop attribute word and / or a commodity attribute word; match, for any shop, attribute information of any shop and / or commodity information in any shop with the target attribute word; and select, as the target shop, a shop in which the target attribute word is matched.

[0182] The electronic device of the embodiment can execute the method of the embodiment shown in Figure 3 The implementation principle and technical effects of the method of the embodiment shown in

[0183] The embodiment of the present application also provides an electronic device, and the structure of the electronic device is the same or similar to the structure of the electronic device shown in Figure 6 The embodiment of the present application also provides an electronic device, and the structure of the electronic device is the same or similar to the structure of the electronic device shown in Figure 6 The embodiment of the present application also provides an electronic device, and the structure of the electronic device is the same or similar to the structure of the electronic device shown in Figure 6The difference between the electronic devices in the illustrated embodiments mainly lies in that the functions implemented by the processors executing the computer programs stored in the memories are different. For the electronic device provided in the embodiments, the processor executes the computer program stored in the memory, and can be used for: in response to a trigger operation of a store recommendation, obtaining a current location of a user; determining a first physical block according to the current location of the user; obtaining a target store associated with the first physical block; and displaying store information of the target store associated with the first physical block on a first page.

[0184] In an optional embodiment, the first page further includes: at least one block switching control, and different block switching controls correspond to different other physical blocks. Based on this, the processor is further configured to: in response to a trigger operation of any block switching control, jump from the first page to a second page, and the second page includes store information of a target store associated with the other physical block corresponding to any block switching control.

[0185] In an optional embodiment, the processor is specifically configured to: according to the block attribute information of each online store, obtain at least one store associated with the first physical block; and according to user behavior data and / or store sales data of the at least one store in a specified period, obtain a target store of an associated media event from the at least one store.

[0186] The electronic device of the embodiments can perform Figure 4 The implementation principles and technical effects of the method of the embodiments are not repeated, and the specific manners of the above related operations have been described in detail in the embodiments related to the method, and will not be described in detail here.

[0187] Correspondingly, the embodiments of the present application also provide a computer readable storage medium storing a computer program, when the computer program is executed by a processor, the processor can implement the steps in the above Figure 2a 、 Figure 3 or Figure 4 the method embodiments.

[0188] Correspondingly, the embodiments of the present application also provide a computer program product, including computer programs / instructions, when the computer programs / instructions are executed by a processor, the processor can implement the steps in the above Figure 2a 、 Figure 3 or Figure 4 the method embodiments.

[0189] The above-described memory can be implemented by any type of volatile or nonvolatile memory devices or a combination thereof, such as static random-access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0190] The above-described communication component is configured to facilitate wired or wireless communication between the device in which the communication component is located and other devices. The device in which the communication component is located can access a wireless network based on a communication standard, such as WiFi, a 2G, 3G, 4G / LTE, 5G, or the like mobile communication network, or a combination thereof. In an example embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast managing system via a broadcast channel. In an example embodiment, the communication component further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on Radio Frequency Identification (RFID) technology, Infrared Data Association (IrDA) technology, Ultra Wide Band (UWB) technology, BlueTooth (BT) technology, and other technologies.

[0191] The above-described display includes a screen, which can include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense a touch, a slide, and a gesture on the touch panel. The touch sensor can not only sense a boundary of a touch or a slide action, but also detect a duration and a pressure associated with a touch or a slide operation.

[0192] The above-described power component provides power to various components of the device in which the power component is located. The power component can include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to the device in which the power component is located.

[0193] The audio component can be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC) that is configured to receive an external audio signal when the device in which the audio component is included is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in a memory or transmitted via the communication component. In some embodiments, the audio component further includes a speaker for outputting audio signals.

[0194] Those skilled in the art will appreciate that embodiments of the present application can be supplied as a method, a system, or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-readable storage media (including, but not limited to, disk memory, Compact Disc Read-Only Memory (CD-ROM), optical memory, and the like) embodying computer usable program code.

[0195] The present application is described in reference to the flowchart illustrations and / or block diagrams according to the embodiments of the present application. It is understood that each flow and / or block in the flowchart illustrations and / or block diagrams, and combinations of flows and / or blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, a special purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the functions specified in the flowchart illustrations and / or block diagrams.

[0196] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions means which implement the function specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the functions specified in the flowchart illustrations and / or block diagrams.

[0197] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more flows and / or blocksFigure 1 the functions specified in the block or blocks.

[0198] In one typical arrangement, the computing device includes one or more processors (Central Processing Units, CPUs), input / output interfaces, network interfaces, and memory.

[0199] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), EPROM, and / or flash memory, etc. The memory is an example of computer readable media.

[0200] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital video disc (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0201] It should also be noted that the terms "comprising," "including," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements in the list, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0202] The above merely provides an example of the present application, and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall fall into the scope of claims of the present application.

Claims

1. A method for recommending store information, characterized in that, include: Responding to the triggering action of store recommendations, obtain user behavior data and / or store sales data of at least one store within a specified time period; Based on user behavior data and / or store sales data of the at least one store within a specified time period, obtain the target store for the associated media event from the at least one store; Using preset copywriting templates, media-enhanced store information for the target store is generated based on media events associated with the target store. The preset copywriting templates include a first template and a second template. The first template is used to populate the description information of the media event and the attribute information of the target store. The second template is used to translate user behavior data and / or store sales data corresponding to at least one product information item to obtain trending copywriting information for at least one product information item. The media-enhanced store information for the target store includes trending copywriting information for at least one product information item and the description information of the media event. The target store's media-based store information is displayed on the first page to recommend the target store to users.

2. The method according to claim 1, characterized in that, Based on user behavior data and / or sales data of the at least one store within a specified time period, the target stores for related media events are obtained from the at least one store, including: Based on user behavior data and / or store sales data of the at least one store within a specified time period, generate access popularity information for the at least one store; Based on the access popularity information of the at least one store, select at least one candidate store that meets the popularity criteria from the at least one store; The at least one candidate store is associated with a known media event from at least one information dimension to obtain the target store associated with the media event.

3. The method according to claim 2, characterized in that, Associating the at least one candidate store with a known media event from at least one information dimension to obtain the target store associated with the media event includes: Extract target attribute words from the descriptive information of known media events, wherein the target attribute words include store attribute words and / or product attribute words; For any candidate store, match the attribute information of the candidate store and / or the product information in the candidate store with the target attribute word; If the target attribute word is matched, any of the candidate stores will be used as the target store associated with the media event.

4. The method according to claim 1, characterized in that, Before generating media-based store information for the target store based on media events associated with the target store, the process also includes: If the number of target stores exceeds a set threshold, the target stores are filtered based on the attribute information of the media events associated with the target stores, the user's product preference information, and / or the attribute information of the target stores.

5. The method according to claim 1, characterized in that, Based on the media events associated with the target store, media-based store information for the target store is generated, including at least one of the following: Based on the correlation between each product information in the target store and the media event, at least one product information that meets the correlation requirements is selected. Based on the description information of the media event, product copy information of the at least one product information is generated as media-based store information. Based on the attribute information of the target store and the description information of the media event, store copy information associated with the media event is generated as media-based store information; Based on the popularity information of each product in the target store, at least one product with popularity information that meets the requirements is selected. Based on the description information of the media event, product copy information of the at least one product is generated as media-based store information.

6. The method according to claim 5, characterized in that, Based on the description information of the media event, product copy information for the at least one product is generated, including: The user behavior data and / or store sales data corresponding to the at least one product information are translated using a preset second copywriting template to obtain the popularity copywriting information corresponding to the at least one product information. The description information of the media event is used as the reason for its popularity to supplement the popularity copy information corresponding to the at least one product information, so as to obtain the product copy information of the at least one product information.

7. The method according to claim 1, characterized in that, The first page displays multimedia store information of the target store to recommend the target store to users, including: Based on preset category tags and the attribute information of the target stores, the target stores are classified to obtain at least one category of target stores; Based on the user's product preference information, the attribute information of the media events associated with the target store, and / or the attribute information of the target store, the at least one type of target store is sorted. According to the sorting results of the at least one type of target stores, the at least one type of target stores are displayed on at least one tab embedded in the first page, wherein each tab corresponds to a category tag.

8. The method according to claim 1, characterized in that, The first page also includes a first redirect control, and the method further includes: In response to the triggering operation of the first jump control, the user jumps from the first page to the second page. The second page displays multiple store information aggregated according to the first aggregation dimension, as well as a second jump control associated with the second aggregation dimension. The second redirect control points to a third page, which includes multiple store information aggregated and displayed according to the second aggregation dimension.

9. A method for recommending store information, characterized in that, include: Retrieve target media events that occurred within a specified time period; Identify the target store associated with the target media event from at least one store; Using preset copywriting templates, media-formatted store information for the target store is generated based on the target media event. The preset copywriting templates include a first template and a second template. The first template is used to fill in the description information of the media event and the attribute information of the target store. The second template is used to translate user behavior data and / or store sales data corresponding to at least one product information to obtain trending copywriting information corresponding to at least one product information. The media-formatted store information for the target store includes trending copywriting information corresponding to at least one product information and the description information of the media event. The media-formatted store information for the target store is displayed on a first page to recommend the target store to users.

10. The method according to claim 9, characterized in that, Retrieve target media events that occurred within a specified time period, including: From at least one media event that occurs within a specified time period, select media events with a popularity greater than a first set popularity threshold and containing target attribute words as target media events; the target attribute words include store attribute words and / or product attribute words.

11. The method according to claim 9 or 10, characterized in that, Identifying the target store associated with the target media event from at least one store includes: Extract target attribute words from the description information of the target media event, the target attribute words including store attribute words and / or product attribute words; For any given store, match the attribute information of that store and / or the product information in that store with the target attribute word; Shops matching the target attribute words are selected as candidate shops, and the target shop is selected from the candidate shops.

12. A method for recommending store information, characterized in that, include: In response to the triggering action of store recommendation, a store recommendation request is sent to the server device; The system receives media-formatted information about a target store returned by the server-side device. The target store is identified by the server-side device as being associated with a media event based on user behavior data and / or sales data of at least one store within a specified time period. The system generates media-formatted store information for the target store based on the media event associated with it, using a preset copywriting template. The preset copywriting template includes a first copywriting template and a second copywriting template. The first copywriting template is used to fill in the description information of the media event and the attribute information of the target store. The second copywriting template is used to translate the user behavior data and / or sales data corresponding to at least one product information to obtain trending copywriting information corresponding to at least one product information. The media-formatted store information of the target store includes trending copywriting information corresponding to at least one product information and the description information of the media event. The target store's media-based store information is displayed on the first page to recommend the target store to users.

13. A method for recommending store information, characterized in that, include: In response to a store recommendation request sent by a terminal device, obtain user behavior data and / or store sales data for at least one store within a specified time period; Based on user behavior data and / or store sales data of the at least one store within a specified time period, obtain the target store for the associated media event from the at least one store; Using preset copywriting templates, media-enhanced store information for the target store is generated based on media events associated with the target store. The preset copywriting templates include a first template and a second template. The first template is used to populate the description information of the media event and the attribute information of the target store. The second template is used to translate user behavior data and / or store sales data corresponding to at least one product information item to obtain trending copywriting information for at least one product information item. The media-enhanced store information for the target store includes trending copywriting information for at least one product information item and the description information of the media event. The media-formatted store information of the target store is sent to the terminal device so that the terminal device can display the media-formatted store information of the target store.

14. An electronic device, characterized in that, include: Memory and processor; The memory is used to store a computer program; the processor, coupled to the memory, is used to execute the computer program to implement the steps of the method according to any one of claims 1-8, 9-11, 12, and 13.

15. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it causes the processor to perform the steps of the method according to any one of claims 1-8, 9-11, 12, and 13.

Images