Commodity recommendation method and device

Abstract

The embodiment of the invention discloses a commodity recommendation method and device. According to the main technical scheme, the method comprises the steps that at least one order item is displayed on an order page, each order item corresponds to at least one order commodity, and a recommendation control associated with the order commodity is displayed for each order item; and in response to an event for triggering the recommendation control detected on the order page, commodity recommendation data is generated, and the commodity recommendation data is used for recommending order commodities associated with the triggered recommendation control. According to the method, a commodity recommendation function is provided for the user, and the user can recommend the commodity after purchasing the commodity, so that other users can purchase the commodity according to the recommendation data of the recommended user, and the difference between the commodity purchased by the user and the expected commodity is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet application, in particular to a commodity recommendation method and device. BACKGROUND

[0002] With the rapid development of Internet and mobile communication technology, various application programs provided for mobile terminals such as mobile phones, tablet computers and the like have also been widely developed. For example, various video playing applications, users can not only watch videos through these video playing applications, but also purchase commodities through the e-commerce platforms provided by these video playing applications.

[0003] At present, when a user purchases a commodity on the e-commerce platform provided by these video playing applications, the user decides whether to purchase the commodity through the commodity detail information displayed by a merchant and the user evaluation content corresponding to the commodity, but this way still has the problem that there is a gap between the commodity purchased by the user and the user's expectation. SUMMARY

[0004] Therefore, the present application provides a commodity recommendation method and device to reduce the gap between the commodity purchased by the user and the user's expectation.

[0005] The present application provides the following solutions:

[0006] In a first aspect, a commodity recommendation method is provided, applied to a production side user end, the commodity recommendation method comprising: displaying at least one order item on an order page, each order item corresponding to at least one order commodity, and respectively displaying a recommendation control associated with the order commodity for each order item; in response to detecting an event of triggering the recommendation control on the order page, generating commodity recommendation data, the commodity recommendation data being used to recommend the order commodity associated with the triggered recommendation control.

[0007] Optionally, in response to detecting the event of triggering the recommendation control on the order page, generating the commodity recommendation data comprises: in response to detecting the event of triggering the recommendation control on the order page, displaying a recommendation reason panel on the order page, the recommendation reason panel being used to determine a recommendation reason of the order commodity associated with the triggered recommendation control, and the recommendation reason panel at least comprising a submission control; and in response to detecting the event of triggering the submission control on the recommendation reason panel, generating the commodity recommendation data.

[0008] Optionally, the recommendation reason panel further comprises at least one recommendation sentence and / or an input area; in response to detecting an event of triggering the submission control on the recommendation reason panel, the product recommendation data is generated, including: in response to detecting that at least one recommendation sentence is selected on the recommendation reason panel, and / or inputting recommendation information of the order product associated with the triggered recommendation control in the input area, and triggering the event of the submission control, the product recommendation data is generated, the product recommendation data comprises a recommendation reason of the order product associated with the triggered recommendation control, and the recommendation reason is determined based on the selected recommendation sentence and / or the recommendation information.

[0009] Optionally, the recommendation reason panel further displays at least one recommendation reason category, the recommendation reason panel displays the at least one recommendation sentence based on the at least one recommendation reason category, and the product recommendation data comprises the at least one recommendation reason category.

[0010] Optionally, the product recommendation data further comprises identification information and product information of the order product associated with the triggered recommendation control, the identification information is used to mark the order product as a recommended product, and the recommended product is a product displayed on a recommended product page of the consumer-side user terminal.

[0011] Optionally, the product recommendation data further comprises information of a recommendation user, the recommendation user is a bound user of a production-side user terminal, and the information of the recommendation user is used to determine a recommended number of times of the order product associated with the triggered recommendation control.

[0012] In a second aspect, a product recommendation method applied to a consumer-side user terminal is provided, the product recommendation method comprising: displaying a product browsing page, the product browsing page being provided with a recommended product entry; in response to detecting an event of triggering the recommended product entry, switching to display a recommended product page, and displaying at least one recommended product on the recommended product page, the recommended product being determined based on product recommendation data generated by a production-side user terminal, the product recommendation data being used to recommend an order product associated with a triggered recommendation control in an order page of the production-side user terminal.

[0013] Optionally, the product recommendation data comprises information of a recommendation user corresponding to the recommended product; and the at least one recommended product is displayed on the recommended product page, including: displaying the at least one recommended product on the recommended product page according to a recommended number of times of each recommended product, wherein the recommended number of times is determined according to the information of the recommendation user corresponding to each recommended product.

[0014] Optionally, the product recommendation data comprises at least one recommendation reason category of the recommended product; and the at least one recommended product is displayed on the recommended product page, including: displaying the at least one recommendation reason category on the recommended product page, and respectively displaying at least one recommended product corresponding to each recommendation reason category.

[0015] Optionally, the at least one recommendation reason category is displayed on the recommended commodity page, and at least one recommended commodity corresponding to each recommendation reason category is displayed respectively for each recommendation reason category, including: sorting the at least one recommendation reason category according to the number of recommended commodities corresponding to each recommendation reason category; and displaying the sorted at least one recommendation reason category on the recommended commodity page, and displaying at least one recommended commodity corresponding to each recommendation reason category respectively for each recommendation reason category.

[0016] Optionally, the at least one recommended commodity is displayed in the form of a commodity card, the commodity card including a commodity preview card and a commodity detail card; the commodity recommendation data further includes at least one recommendation reason corresponding to at least one recommendation reason category; and displaying the at least one recommended commodity on the recommended commodity page includes: displaying the commodity preview card of the at least one recommended commodity on the recommended commodity page; and in response to an event of detecting that the commodity preview card of a target recommended commodity in the at least one recommended commodity is selected on the recommended commodity page, displaying the commodity detail card of the target recommended commodity on the recommended commodity page, the commodity detail card including at least one of commodity information of the target recommended commodity, the number of recommendation users, the recommendation reason corresponding to the target recommended commodity, the store information corresponding to the target recommended commodity, and commodity preview information corresponding to hot-selling commodities in the store.

[0017] Optionally, the commodity recommendation method further includes: in response to detecting a target operation on the commodity information in the commodity preview card or the commodity detail card of the target recommended commodity on the recommended commodity page, switching to a purchase page of the target recommended commodity.

[0018] Optionally, the recommendation user is an associated user of a bound user of the consumption-side user terminal.

[0019] In a third aspect, a commodity recommendation device is provided, applied to a production-side user terminal, and includes: a page display unit configured to display at least one order entry on an order page, each order entry corresponding to at least one order commodity, and a recommendation control associated with the order commodity is displayed respectively for each order entry; an event listening unit configured to listen to events on the order page; and a data generation unit configured to generate commodity recommendation data in response to detecting an event triggering the recommendation control on the order page, the commodity recommendation data being used to recommend the order commodity associated with the triggered recommendation control.

[0020] In a fourth aspect, a commodity recommendation apparatus is provided, applied to a consumer-side user terminal, and includes: a page display unit configured to display a commodity browsing page, the commodity browsing page being provided with a recommended commodity entry; an event listening unit configured to listen to events on the commodity browsing page; and the page display unit is further configured to, in response to detecting an event that the recommended commodity entry is triggered, switch to display a recommended commodity page, and display at least one recommended commodity on the recommended commodity page, the recommended commodity being determined based on commodity recommendation data generated by a production-side user terminal, the commodity recommendation data being used to recommend an order commodity in an order page of the production-side user terminal that is associated with the triggered recommended control.

[0021] In a fifth aspect, a computer-readable storage medium is provided, and the computer-readable storage medium stores a computer program, and the computer program is executed to implement the steps of the method of the first aspect or the second aspect.

[0022] In a sixth aspect, an electronic device is provided, and includes: one or more processors; and a memory associated with the one or more processors, the memory being configured to store program instructions, and the program instructions, when executed by the one or more processors, perform the steps of the method of the first aspect or the second aspect.

[0023] In a seventh aspect, a computer program product is provided, and includes a computer program, and the computer program, when executed, implements the steps of the method of the first aspect or the second aspect.

[0024] According to the embodiments provided in the present application, the following technical effects are disclosed:

[0025] 1) The present application provides a commodity recommendation function for a production-side user terminal, and after a recommended user purchases a commodity, the recommended user can trigger a recommended control associated with an order commodity in at least one order item displayed on an order page to generate commodity recommendation data of the order commodity, thereby recommending the order commodity, so that a consumer-side user terminal can display recommended commodities according to the commodity recommendation data, and a user bound to the consumer-side user terminal can browse and evaluate the displayed recommended commodities, thereby reducing the gap between the purchased commodity and the user's own expectations.

[0026] 2) When the present application provides a commodity recommendation function for a recommended user, if the recommended user triggers a recommended control, a recommendation reason panel can also be displayed on the order page, and the recommended user can submit a recommendation reason for the order commodity associated with the recommended control through the recommendation reason panel, so that a user bound to a consumer-side user terminal can intuitively see the recommendation reason of the recommended commodity, thereby enabling the user bound to the consumer-side user terminal to quickly find a commodity that meets his or her needs.

[0027] 3) The application can also provide at least one recommendation sentence to the recommendation user on the recommendation reason panel, and the recommendation user can quickly submit the recommendation reason for the order commodity associated with the recommendation control by selecting the at least one recommendation sentence; in addition, the input area for inputting the recommendation information can also be provided on the recommendation reason panel, and the recommendation user can input the recommendation information not contained in the recommendation sentence provided on the recommendation reason panel through the input area, so as to meet the personalized expression of the recommendation user and improve the flexibility of the recommendation user in inputting the recommendation reason for the order commodity associated with the recommendation control.

[0028] 4) When the application displays at least one recommendation sentence on the recommendation reason panel, at least one recommendation sentence corresponding to at least one recommendation reason category can be displayed respectively according to the at least one recommendation reason category, so that the recommendation user can select the corresponding recommendation sentence according to the recommendation reason category, thereby improving the recommendation accuracy of the recommendation user for the commodity.

[0029] 5) When the application contains multiple inventory holding unit items of order commodities in one order item, the application can provide the order commodity of each inventory holding unit item with an associated recommendation control, so that the recommendation user can more accurately recommend the order commodity of each inventory holding unit item.

[0030] 6) When the recommendation user triggers the recommendation control, the generated commodity recommendation data can also include identification information and commodity information of the order commodity associated with the recommendation control, so as to mark the order commodity associated with the recommendation control as a recommended commodity, thereby reducing the probability of recommending the same commodity on the consumption side user end; in addition, the information of the recommendation user can also be included in the commodity recommendation data, so that the number of times of being recommended of the recommended commodity can be displayed on the consumption side user end, so that the consumption side user end bound user can evaluate the recommended commodity according to the number of times of being recommended of the recommended commodity, thereby reducing the decision cost of the consumption side user end bound user.

[0031] 7) The application sets a recommended commodity entrance on the commodity browsing page of the consumption side user end, and the consumption side user end bound user can enter the recommended commodity page through the recommended commodity entrance, so as to browse and evaluate the recommended commodity of the production side user end bound user (i.e. the recommendation user), thereby reducing the gap between the commodity purchased by the consumption side user end bound user and the expectation of the consumption side user end bound user.

[0032] 8) The application displays at least one recommended commodity on the recommended commodity page according to the number of times of being recommended of the recommended commodity, so that the consumption side user end bound user can pay more attention to the recommended commodity with more times of being recommended, and more times of being recommended means that more recommendation users approve the recommended commodity, which means that the recommended commodity is closer to the expectation of the consumption side user end bound user, thereby reducing the decision cost of the consumption side user end bound user.

[0033] 9) The application can also display at least one recommendation reason category on the recommended product page, and display at least one recommended product corresponding to each recommendation reason category, so that the consumer-side user-end binding user can intuitively see the recommended products corresponding to each recommendation reason category, thereby improving the efficiency and accuracy of the user's selection of recommended products that match their expectations.

[0034] 10) The application can also sort the recommendation reason categories according to the number of recommended products corresponding to each recommendation reason category, and display the sorted recommendation reason categories and at least one recommended product corresponding to each recommendation reason category, so that the consumer-side user-end binding user can pay more attention to recommendation reason categories with more recommended products, and more recommended products mean that the consumer-side user-end binding user has more options, thereby improving the efficiency and accuracy of the user's selection of recommended products that match their expectations, while also meeting the user's more diverse needs.

[0035] 11) The application can also display at least one recommended product in the form of a product preview card on the recommended product page, which can display more recommended products on the recommended product page, thereby improving the efficiency of the consumer-side user-end binding user's browsing of at least one recommended product. If the user needs to understand the details of a recommended product, they can trigger the product preview card of the recommended product to display detailed information about the recommended product on the recommended product page, thereby enhancing the consumer-side user-end binding user's understanding of the recommended product and further reducing the gap between the goods purchased by the consumer-side user-end binding user and their expectations.

[0036] 12) The application can also enable switching between the recommended product page and the purchase page, so that the consumer-side user-end binding user can trigger the product information in the product detail card or the product preview card of the target recommended product to jump to the purchase page of the target recommended product, thereby improving the user's efficiency in purchasing the target recommended product.

[0037] 13) The recommended user in the application can be an associated user of the consumer-side user-end binding user, thereby improving the reliability of the recommended user's recommended products, and further reducing the gap between the goods purchased by the consumer-side user-end binding user and their expectations.

[0038] Of course, implementing any product of the application does not necessarily require all the advantages described above. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative effort.

[0040] Figure 1 A system architecture diagram applicable to the embodiments of the present application.

[0041] Figure 2 A schematic flowchart of a commodity recommendation method provided by the embodiments of the present application.

[0042] Figure 3 A schematic diagram of an order page provided by the embodiments of the present application.

[0043] Figure 4 A schematic flowchart of another commodity recommendation method provided by the embodiments of the present application.

[0044] Figure 5 A schematic diagram of switching a commodity browsing page to a recommended commodity page provided by the embodiments of the present application.

[0045] Figure 6 A schematic block diagram of a commodity recommendation device provided by the embodiments of the present application.

[0046] Figure 7 A schematic block diagram of another commodity recommendation device provided by the embodiments of the present application.

[0047] Figure 8 A schematic block diagram of an electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the accompanying drawings in the embodiments of the present application. 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 skilled in the art belong to the scope of protection of the present application.

[0049] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "an" and "the" used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0050] It should be understood that the term "and / or" used herein only describes an association relationship of associated objects, which means that there can be three relationships, for example, A and / or B, which can represent three cases of A alone, A and B together, and B alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after it.

[0051] Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if it is determined" or "if (a stated condition or event) is detected" can be interpreted as "when it is determined" or "in response to determining" or "when (a stated condition or event) is detected" or "in response to detecting (a stated condition or event)".

[0052] With the rapid development of the Internet and mobile communication technology, various application programs provided for mobile terminals such as mobile phones, tablet computers, etc. have also been widely developed. For example, various video playing applications, users can not only watch videos through these video playing applications, but also purchase goods through the e-commerce platform provided by these video playing applications. However, in the e-commerce purchase scene provided by the current video playing application, the purchase relationship is limited between the merchant and the consumer, and there is a lack of endorsement based on the social scene of the consumer. Consumers cannot see the goods recommended by other users or their unilateral or bilateral friends and the reasons for the recommendation, and this part of the unexplored e-commerce purchase scene not only can reduce the gap between the goods purchased by consumers and their expectations, so that consumers can buy the goods they want to buy, but also can improve the transaction increment of the e-commerce platform.

[0053] Therefore, the present application provides a new idea. In order to facilitate the understanding of the present application, first, the system architecture based on the present application is described. Figure 1 The system architecture suitable for the embodiments of the present application is shown in Figure 1 The system architecture can include a production side user end, a consumption side user end, a terminal device and a server end.

[0054] Among them, the production side user end and the consumption side user end are arranged in the terminal device. The user end involved in the embodiments of the present application can be a client running on the terminal device, an applet or a Web application running through a browser, etc.

[0055] The terminal device can include, but is not limited to, a smart mobile terminal, a wearable device, a PC (Personal Computer), a smart home device, and the like. The smart mobile terminal can include, for example, a mobile phone, a tablet computer, a notebook computer, a PDA (Personal Digital Assistant), an Internet automobile terminal, and the like. The wearable device can include, for example, a smart watch, smart glasses, a smart bracelet, a VR (Virtual Reality) device, an AR (Augmented Reality) device, a mixed reality device (i.e., a device that can support virtual reality and augmented reality), and the like. The smart home device can include, for example, a smart television, a smart refrigerator with a display, and the like.

[0056] The production side user end can interact with the server end through the network, request and obtain at least one order item from the server end and display, and request and obtain at least one recommended reason category and at least one recommended sentence corresponding to each recommended reason category from the server end and display; the consumption side user end can interact with the server end through the network, request and obtain at least one recommended product, at least one recommended reason category and recommended reason from the server end and display.

[0057] The server end can be a single server, a server group composed of multiple servers, or a cloud server. The cloud server is also called a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of large management difficulty and weak service scalability in traditional physical hosts and virtual private server (VPS, Virtual Private Server) services.

[0058] The server side can send the at least one order item, the at least one recommendation reason category, and the at least one recommendation sentence corresponding to each recommendation reason category to the production side user side in a streaming manner, and the production side user side displays the at least one order item, the at least one recommendation reason category, and the at least one recommendation sentence corresponding to each recommendation reason category while downloading the data stream. Alternatively, the at least one order item, the at least one recommendation reason category, and the at least one recommendation sentence corresponding to each recommendation reason category can be sent to the production side user side in a progressive transmission manner, and the production side user side displays the data after downloading the entire data stream. In addition, other methods can be used to transmit the at least one order item, the at least one recommendation reason category, and the at least one recommendation sentence corresponding to each recommendation reason category to the production side user side, such as providing the at least one order item, the at least one recommendation reason category, and the at least one recommendation sentence corresponding to each recommendation reason category based on a CDN (Content Delivery Network) and transmitting them to the production side user side.

[0059] The server side can send the at least one recommendation item, the at least one recommendation reason category, and the recommendation reason to the consumption side user side in a streaming manner, and the consumption side user side displays the at least one recommendation item, the at least one recommendation reason category, and the recommendation reason while downloading the data stream. Alternatively, the at least one recommendation item, the at least one recommendation reason category, and the recommendation reason can be sent to the consumption side user side in a progressive transmission manner, and the consumption side user side displays the data after downloading the entire data stream. In addition, other methods can be used to transmit the at least one recommendation item, the at least one recommendation reason category, and the recommendation reason to the consumption side user side, such as providing the at least one recommendation item, the at least one recommendation reason category, and the recommendation reason based on a CDN (Content Delivery Network) and transmitting them to the consumption side user side.

[0060] As one of the possible implementations, the production side user side can request the server side for the at least one order item, the at least one recommendation reason category, and the at least one recommendation sentence corresponding to each recommendation reason category, the server side transmits the at least one order item, the at least one recommendation reason category, and the at least one recommendation sentence corresponding to each recommendation reason category to the production side user side, and the production side user side performs product recommendation in the manner provided by the embodiments of the present application; the consumption side user side can request the server side for the at least one recommendation item, the at least one recommendation reason category, and the recommendation reason, the server side transmits the at least one recommendation item, the at least one recommendation reason category, and the recommendation reason to the consumption side user side, and the consumption side user side performs product recommendation in the manner provided by the embodiments of the present application.

[0061] It should be understood that Figure 1 The number of production-side user terminals, consumption-side user terminals, terminal devices and server terminals in the system shown in

[0062] Figure 2 An exemplary flowchart of a commodity recommendation method provided by an embodiment of the present application, which can be executed by a production-side user terminal in the system shown in Figure 1 As shown in Figure 2 The method can include the following steps:

[0063] Step 201: Display at least one order item on an order page, each order item corresponding to at least one order commodity, and for each order item, display a recommendation control associated with the order commodity.

[0064] Step 202: In response to detecting an event triggering the recommendation control on the order page, generate commodity recommendation data, which is used to recommend the order commodity associated with the triggered recommendation control.

[0065] As can be seen from the above flow, by providing the production-side user terminal with the function of commodity recommendation, the present application can generate commodity recommendation data of the order commodity by triggering the recommendation control associated with the order commodity in at least one order item displayed on the order page after the user purchases the commodity, so as to recommend the order commodity, so that the consumption-side user terminal can display the recommended commodity according to the commodity recommendation data, and the user bound to the consumption-side user terminal can browse and evaluate the displayed recommended commodity, thereby reducing the gap between the purchased commodity and the user's expectation, and at the same time, by displaying the recommended commodity for the user bound to the consumption-side user terminal, the probability of the consumption-side user terminal purchasing the recommended commodity can be improved, thereby improving the transaction increment of the e-commerce platform.

[0066] The steps in the above flow and the effects that can be further produced will be described in detail below in conjunction with embodiments.

[0067] First, the above step 201, i.e., "displaying at least one order item on an order page, each order item corresponding to at least one order commodity, and for each order item, displaying a recommendation control associated with the order commodity", will be described in detail in conjunction with an embodiment.

[0068] In the embodiments of the present application, after the production-side user terminal bound user purchases the goods, the user can enter the order page to view the order, and at least one order item can be displayed in the order page. The at least one order item can be an order item generated after the production-side user terminal bound user has received the goods, or an order item generated in the case of non-first purchase but no goods received. For example, an order item generated after the production-side user terminal bound user purchases a certain good again. For the order items generated in the above two cases, a recommendation control associated with the order goods corresponding to each order item can be displayed for each order item, so as to facilitate the production-side user terminal bound user to recommend the order goods. However, if there is a first purchase and no goods received in the at least one order item displayed in the order page, the recommendation control associated with the order goods corresponding to the order item is not displayed, so as to reduce the impact of invalid goods recommendation data generated in this case on the decision of the consumption-side user terminal bound user, thereby further reducing the gap between the goods purchased by the consumption-side user terminal bound user and the user's expectation.

[0069] In one embodiment, the target order item in the at least one order item corresponds to order goods of a plurality of inventory keeping unit items. For each inventory keeping unit item order good, a recommendation control associated with each inventory keeping unit item order good is displayed respectively.

[0070] In the embodiments of the present application, the Stock Keeping Unit (SKU) is a code or number used to uniquely identify goods. Its core function is to distinguish goods of different specifications, attributes, states, etc. Therefore, if there are order goods of multiple SKU items in the order item, a recommendation control associated with each SKU item order good can be displayed for each SKU item order good, so that the production-side user terminal bound user can recommend each SKU item order good in a targeted manner. That is, the number of recommendation controls is the same as the number of SKU items of the order goods in the order item, thereby improving the recommendation accuracy of the order goods.

[0071] For example, if there is only one order item in the order item or there is only one SKU item order item but the number of the SKU item order item is multiple, one recommendation control associated with the one order item or one SKU item order item is displayed, for example, only one pair of trousers is included in the order item, only the recommendation control associated with the trousers is displayed, for example, four same water cups are included in the order item, the four same water cups are one SKU item, and only one recommendation control associated with the water cup is displayed; if there are multiple SKU item order items in the order item, for each SKU item order item, a recommendation control associated with each SKU item order item is displayed, for example, a book and four different SKU items of pens are included in the order item, one recommendation control associated with the book and four recommendation controls associated with the four pens are displayed respectively.

[0072] Figure 3 An order page provided by an embodiment of the present application is shown in the following figure. Figure 3 As shown in (a) of the figure, three order items are displayed on the order page, the first order item includes two same trousers, the trousers are in a received state, and one recommendation control "recommend" associated with the trousers is displayed; the second order item includes a mobile phone, the mobile phone is in an unreceived state, and no recommendation control associated with the mobile phone is displayed; the third order item includes two different SKU items of mobile phones, and the two mobile phones are in a received state, and recommendation controls associated with each mobile phone are displayed respectively.

[0073] Next, the step 202, i.e., "in response to detecting an event of triggering a recommendation control on the order page, generating product recommendation data, the product recommendation data being used for recommending an order item associated with the triggered recommendation control", is described in detail in combination with embodiments.

[0074] In the embodiment of the present application, if an event of triggering a recommendation control is detected on the order page, product recommendation data for an order item associated with the recommendation control can be generated, so as to realize recommending the order item associated with the recommendation control.

[0075] Optionally, the event of triggering the recommendation control can include a production side user end binding user clicking the recommendation control on the order page, triggering the recommendation control through a voice instruction, and the like.

[0076] In one embodiment, the product recommendation data includes identification information and product information of an order item associated with the triggered recommendation control, the identification information is used for marking the order item as a recommended product, and the recommended product is a product displayed on a recommendation product page of a consumption side user end.

[0077] After the recommendation control is triggered, the generated commodity recommendation data can include identification information and commodity information of an order commodity associated with the triggered recommendation control, the identification information is associated with the commodity information of the order commodity, and the order commodity associated with the triggered recommendation control can be marked as a recommended commodity through the identification information. Therefore, when the recommended commodity is displayed on the consumption side user end, the recommended commodity corresponding to the commodity information associated with the identification information can be displayed according to the identification information in the commodity recommendation data and the commodity information of each recommended commodity, thereby reducing the probability of repeatedly recommending the same commodity on the consumption side user end.

[0078] In one embodiment, the commodity recommendation data further includes information of a recommendation user, the recommendation user being a binding user of the production side user end, and the information of the recommendation user being used to determine the number of recommendations of the order commodity associated with the triggered recommendation control.

[0079] After the recommendation control is triggered, the generated commodity recommendation data can further include information of a recommendation user, that is, information of a binding user of the production side user end. For the same commodity, each production side user end can display the commodity, and the binding user of the production side user end can purchase the commodity and recommend the commodity by triggering the recommendation control displayed in the order item corresponding to the commodity. Therefore, after the recommendation control is triggered on the order page, information of each binding user of the production side user end, that is, information of the recommendation user, can be recorded, so that the number of all recommendation users of the order commodity associated with the triggered recommendation control can be determined through the information of the recommendation user, and the number of recommendations of the order commodity can be determined. In the consumption side user end, the number of recommendations of the recommended commodity can be displayed, and the more the number of recommendations, the more the recommended commodity is recognized by more recommendation users. Therefore, the binding user of the consumption side user end can evaluate the recommended commodity according to the number of recommendations of the recommended commodity, so as to not only reduce the decision cost of the binding user of the consumption side user end, but also reduce the gap between the purchased commodity and the expectation of the consumer, so that the consumer can buy the desired commodity. At the same time, the more the number of recommendations of the recommended commodity, the higher the probability of the binding user of the consumption side user end purchasing the recommended commodity, thereby also improving the transaction increment of the e-commerce platform.

[0080] In one embodiment, in response to detecting an event of triggering a recommendation control on an order page, commodity recommendation data is generated, including: in response to detecting an event of triggering a recommendation control on an order page, displaying a recommendation reason panel on the order page, the recommendation reason panel being used to determine a recommendation reason of an order commodity associated with the triggered recommendation control, and the recommendation reason panel at least including a submission control; and in response to detecting an event of triggering the submission control on the recommendation reason panel, generating the commodity recommendation data.

[0081] In order to make the recommended user better deliver his personal opinion on the recommended commodity and improve the effectiveness of his recommendation, the production-side user terminal can provide a recommendation reason panel. If an event triggering the recommendation control is detected on the order page, the recommendation reason panel can be displayed on the order page. The production-side user terminal bound user can determine the recommendation reason of the order commodity associated with the recommendation control triggering the recommendation on the recommendation reason panel and submit the recommendation reason through the submission control on the recommendation reason panel. Therefore, the commodity recommendation data also includes the recommendation reason. For the consumption-side user terminal bound user, the recommendation reason of the recommended commodity can be intuitively seen on the recommended commodity page of the consumption-side user terminal, so that the consumption-side user terminal bound user can quickly find the commodity meeting his needs. This not only reduces the decision cost of the consumption-side user terminal bound user, but also reduces the gap between the commodity purchased by the consumer and his expectation, so that the consumer can buy the commodity he wants to buy.

[0082] In one embodiment, the recommendation reason panel further includes at least one recommendation sentence and / or an input area. In response to detecting an event triggering the submission control on the recommendation reason panel, the commodity recommendation data is generated, including: in response to detecting an event in which at least one recommendation sentence is selected on the recommendation reason panel and / or recommendation information for the order commodity associated with the triggered recommendation control is input in the input area, and the submission control is triggered, the commodity recommendation data containing the recommendation reason for the order commodity associated with the triggered recommendation control is generated. The recommendation reason is determined based on the selected recommendation sentence and / or the recommendation information.

[0083] In order to improve the efficiency of the production-side user terminal bound user in submitting the recommendation reason, at least one recommendation sentence can be generated in advance and displayed on the recommendation reason panel. If an event in which at least one recommendation sentence is selected is detected on the recommendation reason panel, for example, the production-side user terminal bound user clicks at least one recommendation sentence, so that at least one recommendation sentence is in a selected state, and an event in which the submission control on the recommendation reason panel is triggered is detected, commodity recommendation data containing the recommendation reason can be generated. The recommendation reason is the selected recommendation sentence.

[0084] In addition, in order to meet the individualized expression of the production-side user terminal bound user and improve the flexibility of the production-side user terminal bound user in inputting the recommendation reason for the order commodity associated with the recommendation control, the recommendation reason panel can further include an input area. The production-side user terminal bound user can input recommendation information through the input area and trigger the submission control on the recommendation reason panel, so as to generate commodity recommendation data containing the recommendation reason. The recommendation reason is the recommendation information input by the production-side user terminal bound user.

[0085] Optionally, the user bound to the production-side client can either select at least one of the displayed recommendation statements or enter recommendation information in the input area, and then trigger the submit control on the recommendation reason panel to generate product recommendation data containing recommendation reasons. These recommendation reasons include both the selected recommendation statement and the recommendation information entered by the user bound to the production-side client.

[0086] In one embodiment, the recommendation reason panel also displays at least one recommendation reason category, and the recommendation reason panel displays at least one recommendation statement based on at least one recommendation reason category, and the product recommendation data includes at least one recommendation reason category.

[0087] To further improve the accuracy of recommendations for order products associated with recommendation controls by users bound to the production-side client, at least one category of recommendation reasons can be pre-generated and displayed on the recommendation reason panel. Then, at least one recommendation statement can be displayed for each recommendation reason category. When a user bound to the production-side client selects at least one recommendation statement on the recommendation reason panel, the user can determine the category of recommendation reason they are referring to, and then select the corresponding at least one recommendation statement under that category.

[0088] Continue to refer to Figure 3 The production-side user terminal binds users in such Figure 3 Clicking the recommendation control associated with the pants in the first order item on the order page shown in (a) will display the following: Figure 3 The order page shown in (b) is as follows: Figure 3 The order page shown in (b) displays a half-screen recommendation reason panel, the background of which is as follows: Figure 3 The order page shown in (a) is displayed in gray. Figure 3 The recommendation panel shown in (b) includes three categories: "Value for Money Recommendation," "Quality Recommendation," and "Experience Recommendation." Under the "Value for Money Recommendation" category, there are three recommendation statements: "This product offers excellent value for money," "Highly recommended," and "The king of value for money in its category! Functionality, quality, and price are perfectly balanced." Under the "Quality Recommendation" category, there are two recommendation statements: "Superb quality!" and "The fabric is opaque, lint-free, and doesn't attract lint; it's made of pure cotton, of high quality, and thick." Under the "Experience Recommendation" category, there are two recommendation statements: "Super fast shipping!" and "Money-back guarantee if you find it cheaper elsewhere; excellent experience!"

[0089] like Figure 3On the recommendation reason panel shown in (b), a selection state control can be displayed after each recommendation sentence. The production side user terminal binds a user to select a certain recommendation sentence, and the selection state space corresponding to the recommendation sentence is displayed as a selected state. The production side user terminal binds a user to select a recommendation sentence under any recommendation reason category on the recommendation reason panel shown in (b), for example, the production side user terminal binds a user to select "special value for money, strong recommendation" under the "value for money recommendation" category. The selection state control corresponding to "special value for money, strong recommendation" is switched from "O" to Figure 3 In addition, the production side user terminal binds a user to select a recommendation reason category on the recommendation reason panel shown in (b), for example, the production side user terminal binds a user to select "special value for money, strong recommendation" under the "value for money recommendation" category. The selection state control corresponding to "special value for money, strong recommendation" is switched from "O" to In addition, the production side user terminal binds a user to select a recommendation reason category on the recommendation reason panel shown in (b), for example, the production side user terminal binds a user to select "special value for money, strong recommendation" under the "value for money recommendation" category. The selection state control corresponding to "special value for money, strong recommendation" is switched from "O" to Figure 3 In addition, the production side user terminal binds a user to select a recommendation reason category on the recommendation reason panel shown in (b), for example, the production side user terminal binds a user to select "special value for money, strong recommendation" under the "value for money recommendation" category. The selection state control corresponding to "special value for money, strong recommendation" is switched from "O" to Figure 3 In addition, the production side user terminal binds a user to select a recommendation reason category on the recommendation reason panel shown in (b), for example, the production side user terminal binds a user to select "special value for money, strong recommendation" under the "value for money recommendation" category. The selection state control corresponding to "special value for money, strong recommendation" is switched from "O" to Figure 3 In addition, the production side user terminal binds a user to select a recommendation reason category on the recommendation reason panel shown in (b), for example, the production side user terminal binds a user to select "special value for money, strong recommendation" under the "value for money recommendation" category. The selection state control corresponding to "special value for money, strong recommendation" is switched from "O" to

[0090] In an optional implementation, the production side user terminal binds a user to click the submission control on the recommendation reason panel shown in (b), and then returns to the order page shown in (a) to implement recommendation of other order goods. Figure 3 In an optional implementation, the production side user terminal binds a user to click the submission control on the recommendation reason panel shown in (b), and then returns to the order page shown in (a) to implement recommendation of other order goods. Figure 4 In an optional implementation, the production side user terminal binds a user to click the submission control on the recommendation reason panel shown in (b), and then returns to the order page shown in (a) to implement recommendation of other order goods.

[0091] It should be noted that Figure 1 The recommendation reason categories and recommendation sentences shown in (b) are only examples. In fact, other categories of recommendation reason categories and recommendation sentences can also be provided, and / or a certain number of recommendation reason categories and recommendation sentences can also be included. The production side user terminal binds a user to view other recommendation reason categories and recommendation sentences through a sliding operation in a preset direction.

[0092] In an optional implementation, the production side user terminal can define at least one recommendation reason category according to the core demands of consumers in the e-commerce scene in an artificial manner, such as quality, value for money, delivery timeliness, service experience, etc. The existing consumption evaluation content of consumers in the e-commerce scene can also be input into an AI large model to output at least one recommendation reason category through word segmentation, semantic analysis, classification, etc.

[0093] In an alternative embodiment, the production-side user end can also define the corresponding recommendation language for each recommendation reason category in an artificial manner, for example, if the recommendation reason category is quality, the defined recommendation language can be quality super good, quality super high compared with the same type, etc. The determined at least one recommendation reason category and the category information of the commodity can also be input into the AI large model, and the recommendation language under the corresponding recommendation reason category is input through the AI large model.

[0094] It should be noted that the recommendation language displayed on the recommendation reason panel can be a general recommendation language for all commodities, such as "especially worth buying, strongly recommended", "the commodity has a very high cost performance", "the quality is super good!", "the delivery is super fast!", etc. It can also be a recommendation language specific to the order commodity associated with the triggered recommendation control, for example, if the order commodity is trousers, the recommendation language can be "the cloth is not light-transmitting, does not shed hair, does not stick to hair, the material is pure cotton, the material quality is good, the cloth is thick"; it can also display both general recommendation language and specific recommendation language. In addition, the recommendation language displayed on the recommendation reason panel can contain both general recommendation language and specific recommendation language of the order commodity associated with the triggered recommendation control, and also contain other commodity-specific recommendation language, which can be selected by the production-side user end bound user according to demand.

[0095] Figure 4 Another schematic flowchart of a commodity recommendation method provided by the embodiments of the present application is shown in the figure. The method can be executed by the consumer-side user end in the system shown in the figure. As shown in the figure, the commodity recommendation method can include the following steps: Figure 5 Figure 5

[0096] Step 401: display a commodity browsing page, and set a recommended commodity entry on the commodity browsing page.

[0097] Step 402: in response to detecting an event that the recommended commodity entry is triggered, switch to display a recommended commodity page, and display at least one recommended commodity on the recommended commodity page, wherein the recommended commodity is determined based on commodity recommendation data generated by the production-side user end, and the commodity recommendation data is used to recommend the order commodity in the order page of the production-side user end associated with the triggered recommendation control.

[0098] ​​As can be seen from the above process, the application sets a recommended product entry on a product browsing page of a consumption-side user terminal, and a consumption-side user terminal binding user can enter a recommended product page through the recommended product entry, thereby browsing and evaluating the recommended product of a recommended user, so as to reduce the gap between the product purchased by the consumption-side user terminal binding user and the expectation of the consumption-side user terminal binding user. Meanwhile, by displaying the recommended product for the consumption-side user terminal binding user, the probability of purchasing the recommended product by the consumption-side user terminal can be improved, thereby improving the transaction increment of the e-commerce platform.

[0099] The steps in the above process and the effects that can be further produced will be described in detail below with respect to embodiments.

[0100] First, the step 401, i.e., "displaying a product browsing page, and the product browsing page being provided with a recommended product entry", will be described in detail with respect to embodiments.

[0101] In the embodiments of the application, the product browsing page can be the home page of the e-commerce platform of the consumption-side user terminal, and the recommended product entry can be set on the product browsing page, so that the consumption-side user terminal binding user can enter the recommended product page to browse the recommended product.

[0102] In an alternative embodiment, for the same user, the user can act as a production-side user terminal binding user to trigger the recommendation control on the order page to recommend a product to other users, and can also act as a consumption-side user terminal binding user to enter the recommended product page through the recommended product entry set on the product browsing page to browse the product recommended by other users.

[0103] Next, the step 402, i.e., "in response to detecting an event that the recommended product entry is triggered, switching to a recommended product page, and displaying at least one recommended product on the recommended product page, the recommended product being determined based on product recommendation data generated by the production-side user terminal, and the product recommendation data being used to recommend the order product in the order page of the production-side user terminal associated with the triggered recommendation control", will be described in detail with respect to embodiments.

[0104] Figure 5 A schematic diagram of switching the product browsing page to the recommended product page is provided for the embodiments of the application. As shown in (a) of Figure 5 The product browsing page can display products of multiple categories, such as clothing, household supplies, food, outdoor sports, digital products, etc. In addition, a recommended product entry is also displayed, such as the "click here to view recommended products" control displayed on the product browsing page. The consumption-side user terminal binding user can display the recommended product page shown in (b) of Figure 5 by clicking the "click here to view recommended products" control.

[0105] In one embodiment, the product recommendation data includes at least one category of recommendation reasons for the recommended products; displaying at least one recommended product on the recommended product page includes: displaying at least one category of recommendation reasons on the recommended product page, and displaying at least one recommended product corresponding to each category of recommendation reasons.

[0106] On the consumer side, the user client can determine at least one category of recommendation reason based on the product recommendation data generated by the producer side, and display this category on the recommended product page. The wording used for the recommendation reason categories displayed on the recommended product page and the recommendation reason categories displayed on the recommendation reason panel can be the same or different, as long as the recommendation reason categories are identical. For example, if the recommendation reason categories displayed on the recommendation reason panel include quality, cost-effectiveness, delivery time, and service experience, then... Figure 5 As shown in Figure (b), the recommendation reason categories displayed on the recommended product page are "worth buying", "fast delivery", "good quality" and "good experience". For each recommendation reason category, at least one recommended product corresponding to that category is displayed. This allows users on the consumer side to intuitively see the recommended products corresponding to each recommendation reason category. Therefore, it can improve the efficiency and accuracy of users in selecting recommended products that match their expectations.

[0107] In one optional implementation, at least one category of recommendation reasons displayed on the recommended product page can be a category of recommendation reasons for products recommended by users bound to the production side user terminal. If there are no products recommended by users bound to the production side user terminal under a certain category of recommendation reasons, then that category of recommendation reasons can be omitted from the recommended product page to reduce the space occupied on the recommended product page, thereby allowing the recommended product page to display more recommended products, improving the efficiency of users bound to the consumer side browsing recommended products and the user experience.

[0108] In one optional implementation, if there are no products recommended by users on the production side bound to the user terminal under a certain recommendation reason category, then that recommendation reason category can also be displayed on the recommended product page, such as... Figure 5 As shown in (b), no recommended products are displayed under the categories of "Good Quality" and "Good Experience". By displaying complete categories of recommendation reasons, users bound to the consumer side understand the specific types of recommendation reason categories. This allows users bound to the producer side to pay more attention to these recommendation reason categories when recommending products to other users, thereby increasing the diversity of recommended products displayed on the recommended product page.

[0109] In one embodiment, displaying at least one category of recommendation reasons on the recommended products page, and displaying at least one recommended product corresponding to each category of recommendation reasons, includes: sorting at least one category of recommendation reasons according to the number of recommended products corresponding to each category of recommendation reasons; displaying the sorted at least one category of recommendation reasons on the recommended products page, and displaying at least one recommended product corresponding to each category of recommendation reasons.

[0110] At least one recommendation reason category can be displayed on the recommended product page, based on the number of recommended products corresponding to each category. The more recommended products, the higher the corresponding recommendation reason category appears on the recommended product page. A larger number of recommended products means a wider range of choices for users on the consumer side. Therefore, this improves the efficiency and accuracy of users selecting recommended products that match their expectations, while also meeting more diverse user needs. Furthermore, it increases the probability of consumers purchasing recommended products, thereby increasing transaction volume on the e-commerce platform.

[0111] Continue to refer to Figure 5 In case (b), if the number of recommended products corresponding to "Worth Buying" is greater than the number of recommended products corresponding to "Fast Delivery", then "Worth Buying" and its corresponding recommended products will be displayed earlier on the recommended products page, while "Fast Delivery" and its corresponding recommended products will be displayed later.

[0112] Optionally, if multiple recommendation reason categories correspond to the same number of recommended products, the multiple recommendation reason categories corresponding to the same number of recommended products will be displayed randomly.

[0113] In one embodiment, the product recommendation data includes information about the recommending user corresponding to the recommended product; displaying at least one recommended product on the recommended product page includes: displaying at least one recommended product on the recommended product page according to the number of times each recommended product has been recommended, wherein the number of times each recommended product has been recommended is determined based on the information about the recommending user corresponding to each recommended product.

[0114] A higher number of recommendations means that more recommending users approve of the recommended product, which means that the recommended product is closer to the expectations of users bound to the consumer side. Therefore, recommended products with more recommendations can be displayed at the top of the recommended product page according to the number of times they are recommended, thereby reducing the decision-making cost for users bound to the consumer side.

[0115] Continue to refer to Figure 5 In (b), taking the recommended products under the "Worth Buying" category as an example, the recommended products displayed at the front are recommended more often, and the fewer times they are recommended, the further back they are displayed.

[0116] It should be noted that users bound to the consumer-side client can be displayed via swiping in a preset direction. Figure 5 The product recommendation page shown in (b) contains categories of recommendation reasons that are not currently displayed. For example, you can view other categories of recommendation reasons that are not currently displayed by swiping up and down. You can also display recommended products that are not currently displayed under a certain category of recommendation reasons by swiping in a preset direction. For example, you can display recommended products that are not currently displayed under the "Worth Buying" category by swiping left and right.

[0117] In one embodiment, at least one recommended product is displayed in the form of a product card, which includes a product preview card and a product detail card. The product recommendation data also includes at least one recommendation reason corresponding to at least one recommendation reason category. Displaying at least one recommended product on the recommended product page includes: displaying a product preview card of at least one recommended product on the recommended product page; in response to an event that the product preview card of a target recommended product among at least one recommended product is selected on the recommended product page, displaying a product detail card of the target recommended product on the recommended product page, the product detail card including at least one of the following: product information of the target recommended product, the number of recommending users, the recommendation reason of the recommendation reason category corresponding to the target recommended product, the store information corresponding to the target recommended product, and product preview information corresponding to the best-selling products in the store.

[0118] To improve the efficiency of browsing recommended products on the consumer-side client-side, recommended products can be displayed in the form of product cards. For example... Figure 5 As shown in (b), when a user bound to the consumer-side client enters the recommended product page through the recommended product entry point set on the product browsing page, the recommended product page can display product preview cards for all recommended products. The user bound to the consumer-side client can quickly browse the product information of the recommended products through these preview cards. If the user bound to the consumer-side client needs to know more details about a specific recommended product, they can click... Figure 5 The product preview card of the target recommended product shown in (b) displays, as follows: Figure 5 The recommended product page shown in (c) displays a product details card for the target recommended product below the product preview card. This product details card displays a thumbnail of the target recommended product, which may be the same as the thumbnail displayed on the product preview card. The product details card also displays the number of users who recommended the target recommended product ("xxx users recommended this product"), and the product details card also displays, either permanently or by scrolling, the reasons for recommending the target recommended product on the thumbnail. This enhances the understanding of the recommended product among users on the consumer side, thereby further reducing the gap between the purchased product and the user's expectations.

[0119] In addition, in order to further meet the diversified needs of the consumer-side user terminal bound users, such as Figure 6 The recommended commodity page shown in (c) of FIG. 6 further displays the store information corresponding to the target recommended commodity and the commodity preview information corresponding to the hot-selling commodities in the store on the commodity detail card of the target recommended commodity, for example, the commodity preview pictures corresponding to the top three hot-selling commodities in the store.

[0120] In an optional embodiment, as shown in (b) of FIG. 6, when the consumer-side user terminal bound user enters the recommended commodity page through the recommended commodity entry set by the commodity browsing page, the recommended commodity page can display the commodity preview cards of all recommended commodities and display the commodity detail card of the first recommended commodity by default. If the consumer-side user terminal bound user selects to view the commodity details of other recommended commodities, the recommended commodity page shown in (c) of FIG. 6 is displayed, and the commodity detail card of the first recommended commodity is switched to display the commodity detail card of the recommended commodity selected by the consumer-side user terminal bound user. Figure 1 Figure 6 In an optional embodiment, as shown in (b) of FIG. 6, when the consumer-side user terminal bound user enters the recommended commodity page through the recommended commodity entry set by the commodity browsing page, the recommended commodity page can display the commodity preview cards of all recommended commodities and display the commodity detail card of the first recommended commodity by default. If the consumer-side user terminal bound user selects to view the commodity details of other recommended commodities, the recommended commodity page shown in (c) of FIG. 6 is displayed, and the commodity detail card of the first recommended commodity is switched to display the commodity detail card of the recommended commodity selected by the consumer-side user terminal bound user.

[0121] In an embodiment, the commodity recommendation method further comprises: in response to detecting a target operation on the commodity information in the commodity preview card or the commodity detail card of the target recommended commodity on the recommended commodity page, switching to a purchase page of the target recommended commodity.

[0122] The consumer-side user terminal bound user can jump to the purchase page of the target recommended commodity by triggering the commodity information in the commodity detail card of the target recommended commodity or the commodity preview card, thereby improving the efficiency of the user in purchasing the target recommended commodity. For example, the consumer-side user terminal bound user can enter the purchase page of the target recommended commodity by clicking the thumbnail of the target recommended commodity in the commodity detail card of the target recommended commodity. The consumer-side user terminal bound user can understand more detailed commodity information of the target recommended commodity through the purchase page of the target recommended commodity, and can view all user reviews of the target recommended commodity, and the like, so as to improve the accuracy of the decision of the consumer-side user terminal bound user on the target recommended commodity, thereby further reducing the gap between the commodity purchased by the consumer-side user terminal bound user and the expectation of the consumer-side user terminal bound user.

[0123] In an optional embodiment, the recommended user can be a production-side user terminal bound user who has no any association with the consumer-side user terminal bound user, so as to improve the comprehensive understanding of the recommended commodity by the consumer-side user terminal bound user, thereby reducing the gap between the commodity purchased by the consumer-side user terminal bound user and the expectation of the consumer-side user terminal bound user.

[0124] ​In another alternative embodiment, the recommendation user can also bind the associated user of the user of the consumption-side user terminal, for example, the recommendation user is a production-side user terminal binding user that is unilaterally followed or bilaterally followed by the consumption-side user terminal binding user, so as to improve the reliability of the recommended goods, and thus the gap between the goods purchased by the consumption-side user terminal binding user and the self expectation can be further reduced; at the same time, through the friend recommendation, the probability of the consumption-side user terminal purchasing the recommended goods can be further improved, so as to improve the transaction increment of the e-commerce platform. For example, on the recommended goods page, after the recommended reason categories "worth buying", "fast delivery", "good quality", and "good experience" are displayed, "friend-recommended goods with high cost performance", "friend-recommended goods with super-fast delivery", "friend-recommended goods with super-high quality", and "friend-recommended goods with super-good experience" can be displayed. For another example, on the recommended goods page, the number of recommendation users of the target recommended goods "xxx friends recommend this goods" can be displayed on the goods detail card.

[0125] The above describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different than the order in the embodiments and still achieve the desired result. In addition, the processes depicted in the figures do not necessarily require the particular order shown or sequential order to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous or possible.

[0126] According to another aspect, embodiments of a goods recommendation device are provided. Figure 7 A schematic block diagram of a goods recommendation device according to an embodiment of the present application is provided, which is arranged in Figure 1 the production-side user terminal in the architecture shown. As Figure 5 shown, the goods recommendation device 600 mainly includes a page display unit 601, an event listening unit 602, and a data generation unit 603. The main functions of each component unit are as follows:

[0127] The page display unit 601 is configured to display at least one order item on an order page, each order item corresponding to at least one order good, and for each order item, a recommendation control associated with the order good is displayed.

[0128] The event listening unit 602 is configured to listen to events on the order page.

[0129] The data generation unit 603 is configured to generate goods recommendation data in response to detecting an event that triggers the recommendation control on the order page, the goods recommendation data being used to recommend the order good associated with the triggered recommendation control.

[0130] Further, the data generating unit 603 is further configured to, in response to detecting an event of triggering the recommendation control on the order page, display a recommendation reason panel on the order page, the recommendation reason panel being used to determine a recommendation reason of an order item associated with the triggered recommendation control, the recommendation reason panel including at least a submit control; and in response to detecting an event of triggering the submit control on the recommendation reason panel, generate the item recommendation data.

[0131] Further, the recommendation reason panel further includes at least one recommendation sentence and / or an input area; and the data generating unit 603 is further configured to, in response to detecting an event of selecting at least one recommendation sentence on the recommendation reason panel, and / or inputting recommendation information of the order item associated with the triggered recommendation control in the input area, and triggering the submit control, generate the item recommendation data, the item recommendation data including a recommendation reason of the order item associated with the triggered recommendation control, the recommendation reason being determined based on the selected recommendation sentence and / or the recommendation information.

[0132] As one of the optional implementations, the recommendation reason panel further displays at least one recommendation reason category, the recommendation reason panel displays the at least one recommendation sentence based on the at least one recommendation reason category, and the item recommendation data includes the at least one recommendation reason category.

[0133] As one of the optional implementations, a target order item in the at least one order item corresponds to order items of multiple categories, and for each category of order items, a recommendation control associated with each category of order items is displayed respectively.

[0134] As one of the optional implementations, the item recommendation data further includes identification information and item information of the order item associated with the triggered recommendation control, the identification information being used to mark the order item as a recommended item, the recommended item being an item displayed on a recommended item page of the consumer-side user terminal; and the item recommendation data further includes information of a recommendation user, the recommendation user being a bound user of a producer-side user terminal, and the information of the recommendation user being used to determine a recommended times of the order item associated with the triggered recommendation control.

[0135] According to another aspect, embodiments provide a kind of item recommendation device. Figure 8 Another schematic block diagram of the item recommendation device provided by the embodiments of the present application is shown, the device is arranged in ​ the consumer-side user terminal in the architecture shown.As ​ shown, the item recommendation device 700 mainly includes: page display unit 701 and event listening unit 702.The main functions of each component unit are as follows:

[0136] The page display unit 701 is configured to display a commodity browsing page, and the commodity browsing page is provided with a recommended commodity entry.

[0137] The event listening unit 702 is configured to listen to events on the commodity browsing page.

[0138] The page display unit 701 is further configured to, in response to detecting an event that the recommended commodity entry is triggered, switch to display a recommended commodity page, and display at least one recommended commodity on the recommended commodity page, wherein the recommended commodity is determined based on commodity recommendation data generated by a production side user terminal, and the commodity recommendation data is used to recommend an order commodity in an order page of the production side user terminal that is associated with the triggered recommended control.

[0139] Further, the commodity recommendation data includes information of a recommended user corresponding to the recommended commodity; and the page display unit 701 is further configured to display the at least one recommended commodity on the recommended commodity page according to a recommended times of each recommended commodity, wherein the recommended times is determined according to the information of the recommended user corresponding to each recommended commodity.

[0140] Further, the commodity recommendation data includes at least one recommended reason category of the recommended commodity; and the page display unit 701 is further configured to display the at least one recommended reason category on the recommended commodity page, and display the at least one recommended commodity corresponding to each recommended reason category respectively.

[0141] Further, the page display unit 701 is further configured to sort the at least one recommended reason category according to a number of recommended commodities corresponding to each recommended reason category; and display the sorted at least one recommended reason category on the recommended commodity page, and display the at least one recommended commodity corresponding to each recommended reason category respectively.

[0142] Further, the at least one recommended commodity is displayed in the form of a commodity card, and the commodity card includes a commodity preview card and a commodity detail card; the commodity recommendation data further includes at least one recommended reason corresponding to the at least one recommended reason category; and the page display unit 701 is further configured to display the commodity preview card of the at least one recommended commodity on the recommended commodity page; and in response to detecting an event that the commodity preview card of a target recommended commodity in the at least one recommended commodity is selected on the recommended commodity page, display the commodity detail card of the target recommended commodity on the recommended commodity page, wherein the commodity detail card includes at least one of commodity information of the target recommended commodity, a number of recommended users, a recommended reason of a recommended reason category corresponding to the target recommended commodity, shop information corresponding to the target recommended commodity, and commodity preview information of a hot-selling commodity in the shop.

[0143] Further, the page display unit 701 is further configured to switch to a purchase page of the target recommended commodity in response to detecting a target operation on the commodity information in the commodity preview card or the commodity detail card of the target recommended commodity on the recommended commodity page.

[0144] As one of the optional embodiments, the recommended user is an associated user of the binding user of the consumption-side user terminal.

[0145] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. In particular, for system or device embodiments, since they are basically similar to the method embodiments, they are described more simply, and the relevant parts can be referred to the part of the method embodiments. The system and device embodiments described above are only illustrative, and the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e. they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs. Those skilled in the art can understand and implement it without creative labor.

[0146] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.

[0147] In addition, the embodiment of the present application also provides a computer readable storage medium, which stores a computer program, and the program is executed to realize the steps of the method in any one of the preceding method embodiments.

[0148] And an electronic device, comprising:

[0149] One or more processors; and

[0150] A memory associated with the one or more processors, the memory being configured to store program instructions that, when executed by the one or more processors, perform the steps of the method in any one of the preceding method embodiments.

[0151] The application also provides a computer program product comprising a computer program which, when executed, implements the steps of the method according to any one of the preceding method embodiments.

[0152] wherein, ​ The electronic device provided by the embodiment of the application is shown in a schematic block diagram, and can specifically include a processor 810, a video display adapter 811, a disk drive 812, an input / output interface 813, a network interface 814, and a memory 820. The processor 810, the video display adapter 811, the disk drive 812, the input / output interface 813, the network interface 814, and the memory 820 can be communicatively connected through a communication bus 830. The input / output interface 813 can also be referred to as an I / O interface 813.

[0153] The processor 810 can be implemented in a general-purpose CPU, a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute a related program to implement the technical solutions provided by the application.

[0154] The memory 820 can be implemented in a read-only memory (ROM), a random access memory (RAM), a static storage device, a dynamic storage device, or the like. The memory 820 can store an operating system 821 for controlling the operation of the electronic device 800, a basic input / output system (BIOS) 822 for controlling the low-level operation of the electronic device 800. In addition, a web browser 823, a data storage management system 824, and a commodity recommendation apparatus 600 and a commodity recommendation apparatus 700, and the like can also be stored. The commodity recommendation apparatus 600 and the commodity recommendation apparatus 700 can be application programs for implementing the above steps in the embodiment of the application. In summary, when the technical solutions provided by the application are implemented by software or firmware, the related program codes are stored in the memory 820 and executed by the processor 810.

[0155] The input / output interface 813 is configured to connect an input / output module to implement information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. The input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, and the like, and the output device can include a display, a speaker, a vibrator, an indicator, and the like.

[0156] The network interface 814 is configured to connect a communication module (not shown in the figure) to realize the communication interaction between the device and other devices. The communication module can realize communication through wired mode (such as USB, network cable, etc.), or realize communication through wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0157] The bus 830 includes a path for transmitting information between various components (such as the processor 810, the video display adapter 811, the disk drive 812, the input / output interface 813, the network interface 814, and the memory 820) of the device.

[0158] It should be noted that although the above device only shows the processor 810, the video display adapter 811, the disk drive 812, the input / output interface 813, the network interface 814, the memory 820, the bus 830, etc., in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only contain the components necessary to implement the scheme of the present application, and does not have to contain all the components shown in the figure.

[0159] From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be realized by means of software and the necessary general hardware platform. Based on such understanding, the technical solutions of the present application can be embodied in the form of a computer program product, which can be stored in a storage medium such as ROM / RAM, magnetic disk, optical disk, etc., and includes a plurality of instructions for making a computer device (which can be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments of the present application.

[0160] The above describes the technical solutions provided by the present application in detail, and the principles and implementation manners of the present application are described by applying specific examples; the above description of the embodiments is only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range will be changed. In conclusion, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A product recommendation method characterized by comprising: The commodity recommendation method is applied to a production side user end, and the commodity recommendation method comprises the following steps: At least one order item is displayed on an order page, and each order item corresponds to at least one order commodity. A recommendation control associated with the order commodity is displayed for each order item. In response to detecting an event of triggering the recommendation control on the order page, commodity recommendation data is generated, and the commodity recommendation data is used to recommend the order commodity associated with the triggered recommendation control.

2. The product recommendation method according to claim 1, characterized by, The response to detecting the event of triggering the recommendation control on the order page to generate the commodity recommendation data comprises the following steps: In response to detecting the event of triggering the recommendation control on the order page, a recommendation reason panel is displayed on the order page, and the recommendation reason panel is used to determine the recommendation reason of the order commodity associated with the triggered recommendation control. The recommendation reason panel at least comprises a submission control. In response to detecting the event of triggering the submission control on the recommendation reason panel, the commodity recommendation data is generated.

3. The product recommendation method according to claim 2, characterized by, The recommendation reason panel further comprises at least one recommendation sentence and / or an input area. The response to detecting the event of triggering the submission control on the recommendation reason panel to generate the commodity recommendation data comprises the following steps: In response to detecting the event of selecting at least one recommendation sentence on the recommendation reason panel and / or inputting recommendation information of the order commodity associated with the triggered recommendation control in the input area and triggering the submission control, the commodity recommendation data is generated, and the commodity recommendation data comprises the recommendation reason of the order commodity associated with the triggered recommendation control. The recommendation reason is determined based on the selected recommendation sentence and / or the recommendation information.

4. The commodity recommendation method according to claim 3, characterized by, The recommendation reason panel further displays at least one recommendation reason category. The recommendation reason panel displays the at least one recommendation sentence based on the at least one recommendation reason category. The commodity recommendation data comprises the at least one recommendation reason category.

5. The product recommendation method according to any one of claims 1 to 4, characterized in that, The commodity recommendation data further comprises identification information and commodity information of the order commodity associated with the triggered recommendation control. The identification information is used to mark the order commodity as a recommended commodity. The recommended commodity is a commodity displayed on a recommended commodity page of a consumption side user end.

6. The product recommendation method according to any one of claims 1 to 4, characterized in that, The commodity recommendation data further comprises information of a recommendation user. The recommendation user is a binding user of the production side user end. The information of the recommendation user is used to determine the recommended times of the order commodity associated with the triggered recommendation control.

7. A product recommendation method characterized by comprising: The commodity recommendation method is applied to a consumption side user end, and the commodity recommendation method comprises the following steps: A commodity browsing page is displayed. The commodity browsing page sets a recommended commodity entrance. In response to detecting the event of triggering the recommended commodity entrance, the recommended commodity page is switched to be displayed. At least one recommended commodity is displayed on the recommended commodity page. The recommended commodity is determined based on commodity recommendation data generated by a production side user end. The commodity recommendation data is used to recommend an order commodity associated with a triggered recommendation control in an order page of the production side user end.

8. The product recommendation method according to claim 7, characterized by, The commodity recommendation data includes information of a recommended user corresponding to the recommended commodity; and the step of displaying at least one recommended commodity on the recommended commodity page comprises: The at least one recommended commodity is displayed on the recommended commodity page according to a recommended times of each recommended commodity, wherein the recommended times is determined according to the information of the recommended user corresponding to each recommended commodity.

9. The product recommendation method according to claim 7 or 8, characterized in that, The commodity recommendation data includes at least one recommended reason category of the recommended commodity; and the step of displaying at least one recommended commodity on the recommended commodity page comprises: The at least one recommended reason category is displayed on the recommended commodity page, and at least one recommended commodity corresponding to each recommended reason category is displayed respectively.

10. The product recommendation method according to claim 9, characterized in that, The step of displaying at least one recommended reason category on the recommended commodity page and displaying at least one recommended commodity corresponding to each recommended reason category respectively comprises: The at least one recommended reason category is sorted according to a number of recommended commodities corresponding to each recommended reason category; The sorted at least one recommended reason category is displayed on the recommended commodity page, and at least one recommended commodity corresponding to each recommended reason category is displayed respectively.

11. The product recommendation method according to claim 9, characterized in that, The at least one recommended commodity is displayed in the form of a commodity card, the commodity card includes a commodity preview card and a commodity detail card; and the commodity recommendation data further includes at least one recommended reason corresponding to the at least one recommended reason category. The step of displaying at least one recommended commodity on the recommended commodity page comprises: A commodity preview card of at least one recommended commodity is displayed on the recommended commodity page; In response to an event that the commodity preview card of a target recommended commodity in the at least one recommended commodity is selected on the recommended commodity page, a commodity detail card of the target recommended commodity is displayed on the recommended commodity page, the commodity detail card includes at least one of commodity information of the target recommended commodity, a number of recommended users, a recommended reason of a recommended reason category corresponding to the target recommended commodity, shop information corresponding to the target recommended commodity, and commodity preview information of a hot-selling commodity in the shop.

12. The product recommendation method according to claim 11, characterized in that, The commodity recommendation method further comprises: In response to a target operation on the commodity preview card or the commodity detail card of the target recommended commodity, a purchase page of the target recommended commodity is displayed.

13. The product recommendation method according to claim 11, characterized in that, The recommended user is an associated user of a bound user of the consumption-side user terminal.

14. A commodity recommendation device characterized by comprising: The commodity recommendation device is applied to a production-side user terminal, and comprises: A page display unit configured to display at least one order entry on an order page, each order entry corresponding to at least one order commodity, and a recommendation control associated with the order commodity is displayed for each order entry respectively; An event listening unit configured to listen to an event on the order page; A data generation unit configured to generate commodity recommendation data in response to detecting an event triggering the recommendation control on the order page, the commodity recommendation data being used to recommend the order commodity associated with the triggered recommendation control.

15. A commodity recommendation device characterized by comprising: The commodity recommendation device is applied to a consumer-side user terminal and comprises: a page display unit configured to display a commodity browsing page, wherein the commodity browsing page is provided with a recommended commodity entry; an event listening unit configured to listen to events on the commodity browsing page; the page display unit is further configured to, in response to detecting an event in which the recommended commodity entry is triggered, switch to a recommended commodity page, and display at least one recommended commodity on the recommended commodity page, wherein the recommended commodity is determined based on commodity recommendation data generated by a production-side user terminal, and the commodity recommendation data is used to recommend an order commodity associated with a triggered recommendation control in an order page of the production-side user terminal.

16. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed to implement the steps of the commodity recommendation method in any one of claims 1 to 13.

17. An electronic device, comprising: comprise: one or more processors; and a memory associated with the one or more processors, the memory being used to store program instructions, the program instructions being read and executed by the one or more processors to perform the steps of the commodity recommendation method in any one of claims 1 to 13.

18. A computer program product comprising a computer program, characterized in that, The computer program is executed to implement the steps of the commodity recommendation method in any one of claims 1 to 13.

Images