Product recommendation method, device, equipment, storage medium, program product

Abstract

This document provides a product recommendation method, apparatus, device, storage medium, and program product. The method includes: receiving a first message; the first message being used to recommend a first product at a first time; both the first product and a second product corresponding to a first product category; the second product being related to interactive information; the interactive information including interaction information between a user and an intelligent system; the second product having a usage period; the first time being related to the usage period; and outputting the first message through the dialogue function of the intelligent system. Therefore, products can be recommended to users more efficiently and accurately, improving the efficiency and accuracy of product recommendations.

Description

Technical Field

[0001] This document relates to the field of computer technology, and in particular to a product recommendation method, apparatus, device, storage medium, and program product. Background Technology

[0002] In related technologies, product recommendations to users are primarily based on user-initiated recommendation requests. For example, if a user enters "the most popular clothes right now" in the search box, recently best-selling clothing items can be recommended. With the diversification of user needs, how to recommend products to users more efficiently and accurately, and improve the efficiency and accuracy of product recommendations, is one of the issues that needs to be considered. Summary of the Invention

[0003] In one scenario, a product recommendation method, apparatus, device, storage medium, or program product is provided, which can recommend products to users more efficiently and accurately, thereby improving the efficiency and accuracy of product recommendations.

[0004] In a first aspect, a product recommendation method is provided, comprising: receiving a first message; the first message being used to recommend a first product at a first time; both the first product and a second product corresponding to a first product category; the second product being related to interactive information; the interactive information including interactive information between a user and an intelligent system; the second product having a usage period; the first time being related to the usage period; and outputting the first message through the dialogue function of the intelligent system.

[0005] Secondly, a product recommendation device is provided, comprising: a first receiving unit for receiving a first message; the first message for recommending a first product at a first time; both the first product and a second product correspond to a first product category; the second product is related to interactive information; the interactive information includes interactive information between a user and an intelligent system; the second product has a usage period; the first time is related to the usage period; and a first output unit for outputting the first message through the dialogue function of the intelligent system.

[0006] Thirdly, an electronic device is provided, comprising: a processor; and a memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the method described in the first aspect.

[0007] Fourthly, a computer-readable storage medium is provided for storing computer-executable instructions that, when executed by a processor, implement the method described in the first aspect.

[0008] Fifthly, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the method described in the first aspect.

[0009] In one scenario, a first message is received and output through the dialogue function of the intelligent system. This first message is used to recommend a first product at the first moment. Both the first and second products correspond to the first product category. The second product is related to interactive information, including interactions between the user and the intelligent system. The second product has a usage cycle, and the first time is related to that cycle. Therefore, for the second product related to the intelligent system, the first time can be determined based on its usage cycle. This first time is equivalent to the recommendation time for the first product. At this recommendation time, the first product is automatically recommended through the dialogue function of the intelligent system. Since the first and second products correspond to the same product category, this simplifies the user's operation process and improves recommendation efficiency by eliminating the need for the user to actively request recommendations. Furthermore, it improves the accuracy of recommending the first product from both the product category and recommendation time perspectives. Thus, it achieves a more efficient and accurate product recommendation effect, improving both the efficiency and accuracy of product recommendations. Attached Figure Description

[0010] To more clearly illustrate the technical solution, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings in the following description only record some implementation situations. For those skilled in the art, other drawings can be obtained from these drawings without creative effort. Figure 1 This is a schematic diagram illustrating an application scenario for a product recommendation method provided under one particular condition. Figure 2a A flowchart illustrating a product recommendation method provided in one scenario; Figure 2b This is a diagram illustrating the first message provided in one scenario. Figure 2c A diagram illustrating the first message provided in another scenario; Figure 2d This is an illustration of a purchase page for the first product provided in one scenario. Figure 3a This is a diagram illustrating the first message provided in yet another scenario. Figure 3b This is a diagram illustrating the first message provided in yet another scenario. Figure 3c This is a diagram illustrating the first message provided in yet another scenario. Figure 4aThis is a diagram illustrating the first message provided in yet another scenario. Figure 4b This is a diagram illustrating the first message provided in yet another scenario. Figure 4c This is a diagram illustrating the first message provided in yet another scenario. Figure 5a This is a diagram illustrating the second and third messages provided in one scenario. Figure 5b This is a diagram illustrating the second and third messages provided in another scenario; Figure 6 A schematic diagram of a product recommendation device provided under one specific condition; Figure 7 This is a schematic diagram of the structure of an electronic device provided in one scenario. Detailed Implementation

[0011] To enable those skilled in the art to better understand the technical solutions in one or more of the scenarios described below, the technical solutions in one or more of the scenarios described below will be clearly and completely described below in conjunction with one or more accompanying drawings. Obviously, the scenarios described are only some scenarios, not all scenarios. Based on one or more of the scenarios described below, all other implementations obtained by those skilled in the art without inventive effort should fall within the protection scope of this document.

[0012] It is understood that before using any of the technical solutions described below, relevant parties should be informed of the type, scope of use, and usage scenarios of the information involved and their authorization obtained in an appropriate manner in accordance with relevant laws and regulations.

[0013] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware such as electronic devices, applications, servers, or storage media performing the operation of this technical solution, based on the prompt message.

[0014] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0015] It is understood that the above notification and user authorization process is merely illustrative and does not constitute a limitation on this implementation method. Other methods that comply with relevant laws and regulations may also be applied to this implementation method.

[0016] In one scenario, a product recommendation method, apparatus, device, storage medium, or program product is provided, which can recommend products to users more efficiently and accurately, improving the efficiency and accuracy of product recommendations. The product recommendation method can be applied to and executed by a terminal device, which includes, but is not limited to, laptops, tablets, desktop computers, set-top boxes, mobile devices (e.g., mobile phones, portable music players, personal digital assistants, dedicated messaging devices, portable gaming devices), smartphones, smart speakers, smartwatches, smart TVs, in-vehicle terminals, and various other types of terminal devices.

[0017] Figure 1 This is a schematic diagram illustrating an application scenario of a product recommendation method provided in a particular situation, such as... Figure 1 As shown, the scenario includes terminal device 101. Figure 1 In this system, terminal device 101 can be any user's terminal device. Terminal device 101 also displays an interactive interface 1001 for interacting with the intelligent system. Interactive interface 1001 can be the intelligent system's dialogue interface. Users can send text or voice messages to the intelligent system through the dialogue interface, and the intelligent system can also send text or voice messages to users through the dialogue interface. Thus, the intelligent system provides users with the necessary information through dialogue and performs various functions such as image generation, image editing, and video generation. In some cases, because the intelligent system primarily provides information through dialogue, it can also be called a dialogue assistant.

[0018] The aforementioned intelligent system utilizes one or more of AI (Artificial Intelligence) models and intelligent agents for information processing. The various functions described above, such as image generation, image editing, and video generation, are all implemented through AI models and / or intelligent agents. This intelligent system has a corresponding server-side component. In practice, the intelligent system can be deployed on terminal devices, while the AI ​​models and intelligent agents can be deployed on the server-side component. The intelligent system implements the various functions described above by calling the server-side component.

[0019] Figure 2a This is a flowchart illustrating a product recommendation method provided in one scenario, such as... Figure 2a As shown, the method includes: Step S202: Receive a first message; the first message is used to recommend a first product at a first time; both the first product and the second product correspond to the first product category; the second product is related to interactive information; the interactive information includes interactive information between the user and the intelligent system; the second product has a usage period; the first time is related to the usage period of the second product. Step S204: Output the first message through the dialogue function of the intelligent system.

[0020] In one scenario, a first message is received and output through the dialogue function of the intelligent system. This first message is used to recommend a first product at the first moment. Both the first and second products correspond to the first product category. The second product is related to interactive information, including interactions between the user and the intelligent system. The second product has a usage cycle, and the first time is related to that cycle. Therefore, for the second product related to the intelligent system, the first time can be determined based on its usage cycle. This first time is equivalent to the recommendation time for the first product. At this recommendation time, the first product is automatically recommended through the dialogue function of the intelligent system. Since the first and second products correspond to the same product category, this simplifies the user's operation process and improves recommendation efficiency by eliminating the need for the user to actively request recommendations. Furthermore, it improves the accuracy of recommending the first product from both the product category and recommendation time perspectives. Thus, it achieves a more efficient and accurate product recommendation effect, improving both the efficiency and accuracy of product recommendations.

[0021] In step S202 above, the terminal device receives the first message. The terminal device can receive the first message sent by the server corresponding to the intelligent system.

[0022] The first message is used to recommend a first product in a timely manner. The first product is determined based on a second product associated with the intelligent system. The association between the second product and the intelligent system includes: the second product is related to interactive information, and this interactive information includes the interaction information between the user and the intelligent system. Furthermore, both the first and second products correspond to the first product category, and the second product has a corresponding usage period, which is determined in the first message based on the usage period of the second product.

[0023] In one example, the second product is a consumable that can be consumed regularly. For example, the second product includes, but is not limited to, personal care products such as shampoo, facial cleanser, and laundry detergent, or hygiene products such as paper towels.

[0024] The usage period of the second product includes the duration of use from the start to the end of its use. This usage period can be predetermined by the intelligent system. For example, if the second product includes shampoo, based on the assumption that a bottle of shampoo will be used up in approximately 3 months, the usage period of the second product is determined to be 3 months. Of course, when multiple quantities of the second product are purchased, the usage period can also be determined based on the quantity purchased. For example, if the second product includes two bottles of shampoo, based on the assumption that a bottle of shampoo will be used up in approximately 3 months, the usage period of the second product is determined to be 6 months.

[0025] Since the usage cycle of the second product includes the duration of use from the start to the end of use, and the first time is related to the usage cycle, the first product can be recommended accurately at the first time based on the usage cycle of the second product, thus improving the accuracy of the timing of the first product recommendation.

[0026] "First time" refers to the moment when an intelligent system recommends the first product to a user. In one example, since the receiving and output of messages can be considered as real-time actions, the system can receive and output the first message immediately, thus achieving the effect of recommending the first product to the user in the first instance.

[0027] The first timeframe is defined as the period before the end of use for the second product, which is related to the product's lifespan. For example, if a user purchased two bottles of shampoo from the smart system on March 4th, or if the user informed the system via dialogue that they purchased two bottles of shampoo from a certain platform on March 4th, then these two bottles of shampoo are identified as the second product. Based on the average usage period of one bottle of shampoo being three months, the end of use for the second product is determined to be six months later, specifically September 4th. The timeframe N days before this end of use is defined as the first timeframe, where N is a positive integer. In the example above, the first timeframe could be September 1st.

[0028] Since the first product is available before the end of the second product's usage period, and the end of the second product's usage period is related to the second product's usage cycle, it can effectively recommend the first product to the user before the second product's time expires, helping the user to repurchase the product in a timely manner.

[0029] The second product is associated with the intelligent system. The association between the second product and the intelligent system includes: the second product is related to interactive information, and the interactive information includes the interactive information between the user and the intelligent system.

[0030] In one scenario, the aforementioned interactive information includes purchase information, and the second product includes products purchased by the user through the smart system. In this scenario, the aforementioned association can include the user having purchased the second product through the smart system. A user purchasing a second product through the smart system can be categorized into at least two situations: the user purchases the second product within the smart system, or the user purchases the second product through the smart system on a platform outside the smart system. For example, if a user sends the message "Buy me a bottle of shampoo," and the smart system, based on this message, invokes a purchase page within the smart system, then after the user's purchase, the aforementioned second product includes the shampoo purchased by the user, and the second product includes products purchased by the user through the smart system. If the smart system, based on this message, invokes a purchase page on another platform outside the smart system, then after the user's purchase, the aforementioned second product includes the shampoo purchased by the user, and the second product includes products purchased by the user through the smart system on a platform outside the smart system.

[0031] In this scenario, if a user has purchased a product through the intelligent system, that product can be identified as the second product. Based on the user's purchase information, the system can then recommend the corresponding first product to the user, helping them to achieve functions such as product repurchase.

[0032] In one scenario, the aforementioned interactive information includes dialogue messages, through which the intelligent system obtains product information about the second product. This scenario could involve a user sending a dialogue message to the intelligent system, notifying them of a purchase of the second product. For example, a user might have informed the intelligent system via dialogue that they purchased a bottle of shampoo on a certain platform on March 4th. This shampoo establishes a purchase notification relationship with the intelligent system, and since it is a consumable product with a corresponding usage period, it can be identified as the second product. The product information of the second product may include its name, etc.

[0033] In this scenario, if a user informs the intelligent system that they have purchased a certain product through a conversation message, that product can be identified as the second product. Based on the user's conversation message, the system can then recommend the corresponding first product to the user, helping them to achieve functions such as product repurchase.

[0034] It is understood that the aforementioned purchase information and conversation messages are obtained with the user's authorization. For example, a pop-up window is sent to the user to ask if they allow access to the conversation and purchase records between the user and the intelligent system. With the user's permission, the aforementioned purchase information and conversation messages are obtained.

[0035] The first product is the recommended product determined based on the second product. Both the first and second products correspond to the first product category. For example, if the second product includes shampoo, and the corresponding first product category includes personal care products, then the first product is also a personal care product. Similarly, if the second product includes tissues, and the corresponding first product category includes hygiene products, then the first product is also a hygiene product.

[0036] In one scenario, the first product at least partially performs the product functions of the second product. In this scenario, the number of first products can be one or more, and the number of second products can also be one or more; the number of first and second products can be the same or different. The first product can at least partially perform the product functions of the second product. For example, the second product includes shampoo and shower gel, and the first product includes shampoo. Because the first product can at least partially perform the product functions of the second product, it is highly likely that the first product is the product the user needs, thereby improving the accuracy of product recommendations.

[0037] Based on this, the first product and the second product can be the same product in the first product category; or, the first product and the second product can be different products in the first product category, but the first product and the second product have the same product attributes.

[0038] In one scenario, the first product and the second product are identical products within the same product category. In this case, the quantities of the first product and the second product can be the same. For example, if the first product includes a shampoo from brand A, and the second product also includes the same shampoo, the quantity of the second product can be equal to the quantity of the first product. Similarly, if the first product includes both a shampoo and a shower gel from brand A, and the second product also includes both the same shampoo and shower gel, the quantity of the second product can be equal to the quantity of the first product.

[0039] In one scenario, the first product and the second product are different products within the same first product category, and they share the same product attributes. These product attributes include, but are not limited to, at least one of product brand and product function. In this case, the quantities of the first product and the second product can be the same or different. For example, the first product may include one or more shampoos of brand A, and the second product may include one or more shampoos of brand B. The quantity of the second product can be equal to, greater than, or less than the quantity of the first product. The shared product attributes of the first and second products include product function. Similarly, the first product may include one or more shampoos of brand A, and the second product may include one or more different models of shampoo from brand A and one or more shower gels from brand A. The quantity of the second product can be equal to, greater than, or less than the quantity of the first product. The shared product attributes of the first and second products include product brand. Again, the first product may include one or more shampoos of brand A and one or more shower gels of brand A, and the second product may include one or more different models of shampoo from brand A. The quantity of the second product can be equal to, greater than, or less than the quantity of the first product. The shared product attributes of the first and second products include product brand.

[0040] Since the first product and the second product are the same product in the first product category, or the first product and the second product are different products in the first product category, and the first product and the second product have the same product attributes, various forms of the first product can be recommended to the user for the second product, and there is no limit to the quantity relationship between the first product and the second product, so as to meet the user's needs for various products associated with the second product.

[0041] In one scenario, there are multiple first products, and these first products are combined with each other. In this scenario, the number of second products can be one or more, and the quantities of the first and second products can be the same or different. In this scenario, recommending combined first products to users helps them directly purchase the product combination, reducing the time spent searching for the desired products. For example, if the first products include shampoo and shower gel from brand A, and the second products include shampoo from brand B, recommending a shower gel set to the user based on their prior purchase of shampoo reduces the time spent searching for shower gel sets.

[0042] It's worth noting that the quantity of the first product mentioned above can refer to the number of product categories. For example, if the first product includes one type of shampoo and one type of shower gel, and the intelligent system recommends purchasing 3 bottles of shampoo and 1 bottle of shower gel, then the quantity of the first product can be 2. Of course, the intelligent system can also only recommend the category without specifying the purchase quantity for each category. Similarly, the quantity of the second product can refer to the number of product categories. For example, if the second product includes one type of shampoo and one type of shower gel, and the user has historically purchased 2 bottles of shampoo and 2 bottles of shower gel, then the quantity of the second product can be 2.

[0043] Furthermore, the quantity of the first product mentioned above can also refer to the quantity of the first product purchased. For example, if the first product includes a shampoo and a shower gel, and the intelligent system recommends purchasing 3 bottles of shampoo and 1 bottle of shower gel, then the quantity of the first product can be 4. Similarly, the quantity of the second product can refer to the quantity of the second product purchased. For example, if the second product includes a shampoo and a shower gel, and the user has historically purchased 2 bottles of shampoo and 2 bottles of shower gel, then the quantity of the second product can be 4.

[0044] In step S204 above, the first message is output through the dialogue function of the intelligent system. This allows for the immediate output of the first message, achieving the effect of recommending the first product at the earliest possible time.

[0045] In one scenario, the first message is output through the dialogue function of the intelligent system, including: outputting the first message on the dialogue page of the intelligent system, whereby the dialogue page is used to implement the dialogue function of the intelligent system.

[0046] The intelligent system's dialogue function can be implemented through a dialogue page. Upon startup, the intelligent system outputs its first message via text or voice through this page. In one example, when a user starts the intelligent system on the first available day of the month, the system can output a first message, which may be a text or voice message. The user can initiate the intelligent system actively or based on a prompt message.

[0047] In this case, the first message can be output in the form of text or voice on the dialogue page of the intelligent system based on the dialogue function of the intelligent system, so as to achieve the effect of timely recommending the first product to the user.

[0048] In one scenario, the first message is output through the dialogue function of the intelligent system, including: outputting the first message through the voice dialogue function of the intelligent system; the first message includes a voice message; the dialogue function includes a voice dialogue function.

[0049] The intelligent system's dialogue function includes voice dialogue, which can be implemented based on or without a dialogue page. For example, a user sends a voice command to activate the intelligent system. Based on this command, the intelligent system sends a voice message to the user via a pop-up window using the voice dialogue function. In this case, the intelligent system's dialogue page does not need to be displayed. Therefore, the intelligent system can output a first message in voice form, either based on or without a dialogue page. In one example, when the first day arrives, the intelligent system sends an application notification message to the user. This notification message includes the first message, which can be a text message or a voice message, thereby recommending the first product that the user might be interested in.

[0050] In this case, the intelligent system's dialogue function can be used to output the first message, which includes a voice message. The user can choose to activate or deactivate the intelligent system, thereby achieving the effect of timely recommending the first product to the user.

[0051] The first message can be used to express the reasons for recommending the first product. If the first product and the second product are the same product in the first product category, the reason for recommendation is to recommend the second product before it is finished. If the first product and the second product are different products in the first product category, but have the same product attributes, the reason for recommendation is to recommend a product with the same product attributes as the second product before it is finished. If there are multiple first products, and there is a product combination relationship between the various first products, the reason for recommendation is to recommend a combination of products in the first product category before the second product is finished.

[0052] As previously explained, in one scenario, if the first and second products are the same product within the same product category, the first message can be used to recommend the second product before it runs out. For example, if the first product includes shampoo from brand A, and the second product also includes the same shampoo, the first message could be: "Your shampoo is almost finished; a reminder to repurchase it." In this case, the first message can remind users to repurchase the second product, reducing the time users spend actively searching for it and improving the efficiency and accuracy of product recommendations.

[0053] In another scenario, if the first product and the second product are different products within the same product category, but share the same product attributes, the first message can be used to recommend products with the same attributes as the second product before the second product runs out of stock. For example, if the first product includes shampoo from brand A and the second product includes shampoo from brand B, and the common product attribute is product function, the first message could be: "Your shampoo is almost finished; we recommend popular shampoos from other brands." Similarly, if the second product includes shampoo type A from brand A, and the first product includes shampoo type B from brand A and shower gel from brand A, and the common product attribute is brand, the first message could be: "Your shampoo is almost finished; we recommend popular shower gel sets from the same brand." In this case, the first message can remind users to purchase products with the same attributes as the second product, increasing the diversity of products users can buy and reducing the time users spend actively searching for desired products, thus improving the efficiency and accuracy of product recommendations.

[0054] In another scenario, if there are multiple first-product categories with product combination relationships, the first message can be used to recommend product combinations from the first-product category before the second-product runs out. For example, if the first-product category includes shampoo and shower gel from brand A, and the second-product category includes shampoo from brand B, the first message could be: "Your shampoo is almost finished; we recommend a popular shower gel set." In this case, the first message can remind users to purchase product combinations related to the second-product category, reducing the time users spend actively searching and combining products, and improving the efficiency and accuracy of product recommendations.

[0055] As can be seen, different first messages can be displayed for different situations of the first product, so as to accurately describe to users the reasons for recommending the first product in different situations.

[0056] Figure 2b This is a diagram illustrating the first message provided in a given situation, such as... Figure 2b As shown, the first message can be output to the intelligent system's dialogue page: "Your Brand A shampoo is almost finished. There's a promotional offer now, so please remember to repurchase!" Figure 2b The image also shows a purchase card for brand A shampoo. In this example, the first and second products are the same product, both being brand A shampoo.

[0057] Figure 2c A diagram illustrating the first message provided in another scenario, such as Figure 2c As shown, the first message can be output to the intelligent system's dialogue page: "Your A brand shampoo is almost finished. There's a promotion on B brand shampoo bars right now, so please remember to buy some." Figure 2cThe example also shows a purchase card for brand B shampoo bars. In this example, the first and second products are different products with the same function in the same category; the first product includes brand B shampoo bars, and the second product includes brand A shampoo.

[0058] In one scenario, in response to a triggering of a first message, the purchase page for the first product is displayed. In this scenario, the first message includes purchase information for the first product, such as a purchase card for the first product, and the purchase page for the first product is displayed in response to a user's triggering of the first message. Figure 2d This is an illustration of a purchase page for the first product provided in one scenario, such as... Figure 2d As shown, with Figure 2c For example, if a user triggers the purchase card for the first product, the smart system will display the purchase page for the first product, and the user can purchase or browse the first product based on this purchase page. Figure 2d The first product in the company includes shampoo bars from brand B.

[0059] Therefore, based on the above description, for a second product that a user needs to repurchase regularly, the intelligent system can proactively remind the user to repurchase according to the usage cycle of the second product. When reminding the user to repurchase, it can remind the user to repurchase the same product, or other products with the same product attributes and belonging to the same product category, or even remind the user to repurchase product combinations. This eliminates the need for the user to actively search for products and improves the efficiency of product recommendation.

[0060] In some cases, when there are multiple quantities of the first product and there are product combination relationships between the various first products, the individual first products are determined in the following way: Based on the second product, at least one first product is determined from among the products corresponding to the first product category; Based on the product portfolio relationship, a product is selected from the products corresponding to the first product category; the selected product is used to combine with at least one of the first products mentioned above based on the product portfolio relationship; each first product includes the selected product.

[0061] The process of determining the first product can be executed by the server corresponding to the intelligent system, or it can be executed by the intelligent system itself.

[0062] The number of recommended first products can be multiple, and these first products can be recommended to the user in the form of a product combination through a first message. When determining each first product, at least one first product can be selected from the products corresponding to the first product category, based on the second product. For example, if the second product includes shampoo and the first product category includes personal care products, the second product can be selected as the first product from the personal care products category. Alternatively, a shampoo with the same product attributes as the second product, such as function or brand, can be selected as at least one first product. Next, based on product combination relationships, products are selected from the products corresponding to the first product category. The selected products are used to combine with the at least one first product determined above, based on the product combination relationships. Each first product includes the selected product, and of course, also includes the at least one first product determined above.

[0063] As can be seen, in this method, at least one first product can be determined from the products corresponding to the first product category based on the second product. This first product can be called the benchmark product. Based on the product combination relationship, products are selected from the products corresponding to the first product category. The selected products are used to combine with the benchmark product based on the product combination relationship. Each first product includes the selected product and the benchmark product, so that each first product is recommended to the user in the form of a product combination, thereby achieving the effect of recommending product combinations based on the second product and improving the richness of the recommended products.

[0064] Product portfolio relationships can include one or more of the following: bundled use relationships, promotional bundled relationships, and new product bundled relationships. The primary product can be determined based on these relationships.

[0065] In some cases, product combination relationships include pairing relationships; the above-mentioned selection of products from the various products corresponding to the first product category based on product combination relationships includes: selecting products from the various products corresponding to the first product category based on pairing relationships; the selected products are used in combination with at least one first product determined above.

[0066] A combination usage relationship refers to the ability of multiple products to be used together. Based on this relationship, products can be selected from the various products within a first product category. These selected products are used in combination with at least one of the aforementioned first products. For example, if the aforementioned first products include shampoo, and the first product category includes personal care products, then within the personal care products, a hair growth serum is identified as a product that can be used in combination with shampoo.

[0067] Therefore, in this method, products can be selected from the various products corresponding to the first product category based on the pairing relationship. The selected products are used in combination with at least one of the first products determined above. Thus, it not only achieves the effect of reminding users to repurchase products, but also achieves the effect of recommending product combinations to users based on the pairing relationship, thereby improving the accuracy of product recommendations.

[0068] In some cases, product portfolio relationships include new product portfolio relationships; the above-mentioned selection of products from each product corresponding to the first product category based on product portfolio relationships includes: selecting products from each product corresponding to the first product category based on new product portfolio relationships; the release time of the selected products is less than the first time period.

[0069] A new product portfolio relationship refers to a combination of multiple relationships where some or all of the products are new products. The new product's release time since its initial release is less than the initial release time. For example, the new product's release time since its initial release is within one month. Release time can be understood as the product's sales duration.

[0070] Products can be selected from the various products corresponding to the first product category based on the new product combination relationship. The time since the selected product's release has been less than the first time period. The selected product and the aforementioned first product are related by at least one of the following conditions, including but not limited to: the selected product has the same function as the aforementioned first product; or the selected product and the aforementioned first product can be used together. For example, the aforementioned first product includes shampoo A, the first product category includes personal care products, and the recently released hair growth serum or the recently released shampoo B can be selected from the personal care products.

[0071] Therefore, in this method, products can be selected from each product corresponding to the first product category based on the new product combination relationship. The time since the selected products were released is less than the first time. Therefore, it not only reminds users to repurchase products, but also recommends new products to users based on the new product combination relationship, thus improving the accuracy of product recommendations.

[0072] In some cases, product combination relationships include preferential combination relationships; the above-mentioned selection of products from various products corresponding to the first product category based on product combination relationships includes: selecting products from various products corresponding to the first product category based on preferential combination relationships; the selected products have preferential information when purchased together with at least one of the above-mentioned first products.

[0073] A discount bundle relationship refers to the ability to purchase multiple products together to enjoy a discount. Based on the discount bundle relationship, products can be selected from various products within a first product category, and the selected products, when purchased together with at least one of the aforementioned first products, will receive a discount. For example, if the first product identified above includes shampoo, and the first product category includes personal care products, then a personal care product such as conditioner, which offers a discount when purchased together with the shampoo, can be selected.

[0074] Therefore, in this method, products can be selected from various products corresponding to the first product category based on the discount combination relationship. The selected products have discount information when purchased together with at least one of the first products mentioned above. Thus, it not only achieves the effect of reminding users to repurchase products, but also achieves the effect of recommending discounted product combinations to users based on the discount combination relationship, thereby improving the accuracy of product recommendations.

[0075] As mentioned earlier, product combination relationships include one or more of the following: bundled use relationships, preferential combination relationships, and new product combination relationships. The preceding section described the specific process of including one product combination relationship. When a product combination relationship includes multiple relationships, products that can be combined with at least one of the aforementioned first products can be determined based on these multiple relationships. For example, firstly, candidate products are determined based on one relationship within the product combination relationship, and then, based on other relationships within the product combination relationship, products that can be combined with at least one of the aforementioned first products are determined from among the candidate products.

[0076] Taking product combination relationships, including bundled use relationships and discount bundled relationships, as examples, based on the bundled use relationship, products that can be used in combination with at least one of the aforementioned first products can be selected from among the products corresponding to the first product category as candidate products. Based on the discount bundled relationship, products with discount information that can be purchased together with at least one of the aforementioned first products can be selected from among the candidate products as the first product. Taking product combination relationships, including bundled use relationships and new product bundled relationships, as examples, based on the bundled use relationship, products that can be used in combination with at least one of the aforementioned first products can be selected from among the products corresponding to the first product category as candidate products. Based on the new product bundled relationship, products whose release duration is within the first time period can be selected from among the candidate products as the first product. Cases involving multiple product combination relationships are not elaborated here; please refer to the description in that section.

[0077] Based on the second product, at least one first product is determined from among the products corresponding to the first product category. This first product can be the same as the second product, or it can be a different product with the same product attributes as the second product. Product attributes include, but are not limited to, at least one of brand and product function.

[0078] Figure 3aFor example, a diagram illustrating the first message provided in yet another scenario. Figure 3a As shown, the first message displayed on the intelligent system's dialogue page is: "Your Brand A shampoo is almost finished. You can click the card below to purchase a shampoo and conditioner set." Figure 3a This combination includes shampoo and conditioner from brand A. Figure 3a The image also illustrates the purchase card for this combination. In this example, the first product includes the second product, as well as products used in conjunction with the second product.

[0079] Figure 3b For example, a diagram illustrating the first message provided in yet another scenario. Figure 3b As shown, the first message can be output in the dialogue page of the intelligent system: "Your A brand shampoo is almost finished. We've recently launched a new hair oil. You can click the card below to purchase it together." Figure 3b This set includes shampoo from brand A and hair oil from brand A. Figure 3b The image also illustrates the purchase card for this combination. In this example, the first product includes the second product, as well as a new product that is used in conjunction with the second product.

[0080] Figure 3c For example, a diagram illustrating the first message provided in yet another scenario. Figure 3c As shown, the first message can be output in the dialogue page of the intelligent system: "Your A brand shampoo is almost finished. There is a discount promotion when you buy bath oil together. You can click the card below to buy it together." Figure 3c This combination includes shampoo from brand A and body oil from brand A. Figure 3c The document also illustrates the purchase card for this combination. The first product includes the second product, as well as products that offer discounts when purchased together with the second product.

[0081] Figure 4a For example, a diagram illustrating the first message provided in yet another scenario. Figure 4a As shown, the first message displayed on the intelligent system's dialogue page is: "Your Brand A shampoo is almost finished. You can click the card below to purchase a shampoo and conditioner set." Figure 4a This combination includes shampoo and conditioner from brand B. Figure 4a The image also illustrates the purchase card for this combination. In this example, some of the first and second products share the same product attributes (product functions), and the various first products can be used together.

[0082] Figure 4b For example, a diagram illustrating the first message provided in yet another scenario. Figure 4bAs shown, the first message can be output in the intelligent system's dialogue page: "Your A brand A shampoo is almost finished. We've also recently launched a new hair oil. You can click the card below to purchase it together." Figure 4b This set includes shampoo (model B) from brand A and hair oil from brand A. Figure 4b The image also illustrates the purchase card for this combination. In this example, some of the first and second products share the same product attributes (product brand), and the various first products can be combined based on the new product combination relationship.

[0083] Figure 4c For example, a diagram illustrating the first message provided in yet another scenario. Figure 4c As shown, the first message can be output in the intelligent system's dialogue page: "Your A brand A shampoo is almost finished. There's a discount promotion when you buy body oil together. You can click the card below to buy it together." Figure 4c This set includes shampoo (model B) from brand A and body oil from brand A. Figure 4c The example also illustrates the purchase card for this combination. In this example, some of the first and second products share the same product attributes (product brand), and the various first products can be combined based on their respective discount combinations.

[0084] Before sending the first message, it's necessary to determine not only the first product but also the recommendation time for that product, i.e., the "first time." In some cases, the "first time" is determined in the following ways: If the first product has relevant promotional information before the end time of the second product's use, the first time shall be determined according to the promotional period of the relevant promotional information. If the first product does not have relevant promotional information before the end time of the second product's use, the first time will be determined based on the end time of the second product's use.

[0085] The process of determining the first moment can be executed by the corresponding server of the intelligent system, or it can be executed by the intelligent system itself.

[0086] In this method, it is determined whether the first product has relevant promotional information before the end time of the second product's use. If it does, the first time is determined based on the promotional period of the relevant information; for example, the first time includes the promotional period or the time before the promotional period. If it does not have promotional information, the first time is determined based on the end time of the second product's use; for example, the first time includes the end time of the second product's use or the time before the end time of its use. In this method, the first time determined when the first product has a promotion is earlier than or equal to the first time determined when the first product does not have a promotion, thereby achieving the effect of recommending the first product in advance when it has a promotion.

[0087] In one specific implementation, a second duration and a third duration can be set, with the second duration being longer than the third duration. A first time range preceding the usage end time is determined based on the second and third durations. The start time of the first time range is preceding the usage end time and is two durations away from the usage end time, while the end time of the first time range is preceding the usage end time and is three durations away from the usage end time.

[0088] Next, determine whether the first product within the first time frame has relevant promotional information. Based on the determination result, the first time frame is determined.

[0089] In one example, a user purchased a bottle of shampoo on March 4th through the smart system. The shampoo has a usage period of 3 months, so the usage end date is June 4th. The second usage period is set to 1 month, and the third usage period to 3 days. Since the first product category includes this same shampoo, it is determined whether the shampoo was offered at a discount between May 4th and June 1st.

[0090] If it is determined that the first product within the first time frame has relevant promotional information, then the promotional period of the relevant promotional information is determined. This promotional period can include any effective time of the relevant promotional information, such as the start time of the promotion. Since the relevant promotional information is within the first time frame, the promotional period of the relevant promotional information is also within the first time frame. When any effective time of the relevant promotional information is within the first time frame, the promotional period of the relevant promotional information is determined to be within the first time frame. Determining the first time based on the promotional period can be done by defining the promotional period as the first time, or by defining the period M days prior to the promotional period as the first time, where M is a positive integer.

[0091] If it is determined that the first product does not have relevant promotional information within the first time frame, then the first time frame is determined based on the end time of the first time frame. The end time of the first time frame is located before the end time of the second product's usage and is three hours away from that end time. Therefore, the end time of the first time frame can be determined as the first time frame.

[0092] In the above method, the first time period is used as an observation window to see if the first product has a discount. If the first product does not have a discount when the observation window ends, the first time is determined according to the end time of the observation window. This achieves the effect of reminding users to purchase the first product in advance after it is determined that the first product has a discount, and also reminding users to purchase the first product in a timely manner after it is determined that the first product does not have a discount.

[0093] In some cases, considering that the first product is determined based on the second, the first product is determined in the following ways: If there are relevant promotional offers for the second product before the end of its usage period, the first time shall be determined based on the promotional period of the relevant promotional offers. If the second product does not have relevant promotional information before the end of its usage period, the first time will be determined based on the end of the second product's usage period.

[0094] The difference between this method and the previous one is that the judgment target is changed from the first product to the second product. The first time and the first product are determined based on the discount information of the second product before its expiration date. If the second product has discount information before its expiration date, the first time can be determined based on the discount period, and the first product can be determined based on the second product. If the second product does not have discount information before its expiration date, the first time can be determined based on the expiration date of the second product, and the first product can be determined based on the second product. The first time determined when the second product has a discount is earlier than or equal to the first time determined when the second product does not have a discount.

[0095] In the above process, the first product can be determined first, followed by the first time, or vice versa. After determining the first product and the first time, a first message is output on the intelligent system's dialogue page at the first time, recommending the first product to the user immediately. Based on this time-based product recommendation approach, other scenarios can also be implemented: determine the user's time-related first event, associate the first event with the intelligent system, and output a dialogue message to the user before or when the time corresponding to the first event arrives. This dialogue message is used to recommend products related to the first event before or when the time corresponding to the first event arrives. The association between the first event and the intelligent system can include: the user has previously informed the intelligent system about information related to the first event. For example, if the user has informed the intelligent system that they need to travel on a certain date, then essential travel items will be recommended to the user before that date. When recommending products related to the first event, one or more products can be recommended, and these multiple products can be combined based on one or more of the product combination relationships described above.

[0096] In addition, the above-mentioned method process also includes: In response to a second message sent to the intelligent system, a third message is output through the dialogue function of the intelligent system; the second message is used to request recommendations for products in a second product category; the second product category may be the same as or different from the first product category; the third message is used to recommend a product combination; the product combination includes at least a third product and a fourth product; the third product and the fourth product correspond to the second product category; the third message is used to recommend the third product and the fourth product according to the combination relationship between the third product and the fourth product.

[0097] In this method, the user can send a second message to the intelligent system, requesting recommendations for products in a second product category. This second product category can be the same as or different from the first product category. The intelligent system then outputs a third message to the user, similar to the method used to output the first message. This third message recommends product combinations, each including at least two products. Each product corresponds to a second product category, and the products are combined based on any one or more of the aforementioned product combination relationships. The third message recommends products according to these combination relationships. For example, using a third and fourth product as an example, where both products correspond to the second product category, the third message recommends the third and fourth products based on their combination relationship.

[0098] Figure 5a This is a diagram illustrating the second and third messages provided in a given scenario, such as... Figure 5a As shown in the example, the second message includes: "Please recommend camping equipment." The intelligent system determines the second product category as camping supplies, and based on the aforementioned combination relationships, identifies multiple products as tents, sleeping bags, and lights. The intelligent system outputs a third message to the user, recommending a product combination consisting of tents, sleeping bags, and lights. The third message also describes specific usage methods based on the combination relationships between the tents, sleeping bags, and lights. For example, the third message could be: "I recommend camping equipment consisting of tents, sleeping bags, and lights. Using these three together can meet camping needs in different scenarios." The third message can also provide separate purchase options for each product, or a combined purchase option for the product combination.

[0099] Figure 5b This is a diagram illustrating the second and third messages provided in another scenario, such as... Figure 5b As shown in another example, the second message includes: "Please recommend skincare products." The intelligent system determines the second product category as personal care products and, based on the aforementioned discount combination relationship, identifies multiple products as toner, lotion, and cream. The intelligent system outputs a third message to the user, recommending a product combination consisting of toner, lotion, and cream. The third message also provides specific discount information based on the discount combination relationship between toner, lotion, and cream. For example, the third message could be: "I recommend a skincare set consisting of toner, lotion, and cream; there's a discount when you buy all three together." The third message can also provide separate purchase options for each product, or a combined purchase option for the product combination.

[0100] In the above method, when a user requests recommendations for products in the second product category, the system can recommend product combinations corresponding to the second product category, achieving the effect of recommending product combinations based on user needs and eliminating the tedious operation of users searching for each product individually.

[0101] It's worth noting that the above examples use physical products (products one, two, three, and four). These products can also be virtual products, such as membership cards for applications with a usage period. Examples of virtual products will not be repeated here; they can be derived from the principles described above, and virtual products are also within the scope of this description.

[0102] In summary, the system receives a first message and outputs it through the dialogue function of the intelligent system. This first message is used to recommend a first product immediately. Both the first and second products correspond to the first product category. The second product is related to interactive information, including interactions between the user and the intelligent system. The second product has a usage cycle, and the first time is related to this cycle. Therefore, for the second product related to the intelligent system, the first time can be determined based on its usage cycle. This first time is equivalent to the recommendation time for the first product. At this recommendation time, the first product is automatically recommended through the dialogue function of the intelligent system. Since the first and second products correspond to the same product category, this simplifies the user's operation process and improves recommendation efficiency by eliminating the need for the user to actively request recommendations. Furthermore, it improves the accuracy of recommending the first product by considering both product category and recommendation time. Thus, it achieves a more efficient and accurate product recommendation effect, improving both the efficiency and accuracy of product recommendations.

[0103] Figure 6 This is a schematic diagram of the structure of a product recommendation device provided in one scenario, such as... Figure 6 As shown, the device includes: The first receiving unit 61 is used to receive a first message; the first message is used to recommend a first product at a first time; the first product and the second product both correspond to a first product category; the second product is related to interactive information; the interactive information includes interactive information between the user and the intelligent system; the second product has a usage period; the first time is related to the usage period. The first output unit 62 is used to output the first message through the dialogue function of the intelligent system.

[0104] Optionally, the first product at least partially implements the product functions of the second product.

[0105] Optionally, the first product and the second product are the same product in the first product category; or, the first product and the second product are different products in the first product category, but the first product and the second product have the same product attributes.

[0106] Optionally, there may be multiple first products, and there may be product combination relationships between the various first products.

[0107] Optionally, the usage period of the second product includes the duration of use from the start of use to the end of use.

[0108] Optionally, the first time is located before the end time of use of the second product; the end time of use of the second product is related to the usage cycle of the second product.

[0109] Optionally, the interactive information includes purchase information; the second product includes products purchased by the user through the intelligent system.

[0110] Optionally, the interactive information includes dialogue messages; the intelligent system obtains product information of the second product through the dialogue messages.

[0111] Optionally, the first output unit 62 is specifically used to: output the first message on the dialogue page of the intelligent system; the dialogue page is used to implement the dialogue function.

[0112] Optionally, the first output unit 62 is specifically configured to: output the first message through the voice dialogue function of the intelligent system; the first message includes a voice message; and the dialogue function includes the voice dialogue function.

[0113] Optionally, the first message is used to indicate a recommendation reason for the first product; if the first product and the second product are the same product in the first product category, the recommendation reason is used to indicate that the second product is recommended before its use ends; if the first product and the second product are different products in the first product category, but have the same product attributes, the recommendation reason is used to indicate that a product with the same product attributes as the second product is recommended before its use ends; if there are multiple first products, and there is a product combination relationship between the various first products, the recommendation reason is used to indicate that a product combination in the first product category is recommended before the second product is used up.

[0114] Optionally, the display unit is configured to display the purchase page of the first product in response to a triggering of the first message.

[0115] Optionally, it further includes a second output unit, configured to: output a third message through the dialogue function in response to a second message sent to the intelligent system; the second message is used to request recommendations for products in a second product category; the second product category may be the same as or different from the first product category; the third message is used to recommend a product combination; the product combination includes at least a third product and a fourth product; the third product and the fourth product correspond to the second product category; the third message is used to recommend the third product and the fourth product according to the combination relationship between the third product and the fourth product.

[0116] Optionally, each of the first products is determined by: determining at least one first product among the products corresponding to the first product category based on the second product; selecting a product among the products corresponding to the first product category based on the product combination relationship; the selected product is used to combine with the at least one first product based on the product combination relationship; each of the first products includes the selected product.

[0117] Optionally, the product combination relationship includes a pairing relationship; the step of selecting a product from each product corresponding to the first product category based on the product combination relationship includes: selecting a product from each product corresponding to the first product category based on the pairing relationship; the selected product is used in combination with the at least one first product.

[0118] Optionally, the product portfolio relationship includes a new product portfolio relationship; the step of selecting a product from each product corresponding to the first product category based on the product portfolio relationship includes: selecting a product from each product corresponding to the first product category based on the new product portfolio relationship; the time elapsed since the selected product was published is less than the first time elapsed.

[0119] Optionally, the product combination relationship includes a discount combination relationship; the step of selecting a product from each product corresponding to the first product category based on the product combination relationship includes: selecting a product from each product corresponding to the first product category based on the discount combination relationship; the selected product has discount information when purchased together with at least one of the first products.

[0120] Optionally, the first time is determined in the following ways: if the first product has relevant discount information before the end time of use of the second product, the first time is determined according to the discount period of the relevant discount information; if the first product does not have relevant discount information before the end time of use of the second product, the first time is determined according to the end time of use of the second product.

[0121] It is evident that, for the second product related to the intelligent system, the first time can be determined based on the usage cycle of the second product. This first time is equivalent to the recommendation time of the first product. At the recommendation time of the first product, the first product is automatically recommended through the dialogue function of the intelligent system. The first product and the second product correspond to the same product category. Thus, on the one hand, the user does not need to actively provide a recommendation request, simplifying the user operation process when recommending products and improving the efficiency of product recommendation. On the other hand, the accuracy of recommending the first product is improved from both the product category and recommendation time aspects. Therefore, the effect of recommending products to users more efficiently and accurately is achieved, improving the efficiency and accuracy of product recommendation.

[0122] The product recommendation device described above can realize each process of the product recommendation method described above and achieve the same effect and function, which will not be repeated here.

[0123] Figure 7 This is a schematic diagram of the structure of an electronic device provided in one scenario, such as... Figure 7 As shown, electronic devices can vary considerably due to differences in configuration or performance. They may include one or more processors 701 and memories 702, with the memory 702 storing one or more application programs or data. The memory 702 can be temporary or persistent storage. The application programs stored in the memory 702 may include one or more modules (not shown), each module including a series of computer-executable instructions from the electronic device. Furthermore, the processor 701 may be configured to communicate with the memory 702, executing the series of computer-executable instructions stored in the memory 702 on the electronic device. The electronic device may also include one or more power supplies 703, one or more wired or wireless network interfaces 704, one or more input or output interfaces 705, one or more keyboards 706, etc.

[0124] In one specific scenario, the electronic device includes a processor; and a memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the following process: Receive a first message; the first message is used to recommend a first product at a first time; both the first product and the second product correspond to a first product category; the second product is related to interactive information; the interactive information includes interactive information between the user and the intelligent system; the second product has a usage period; the first time is related to the usage period. The first message is output through the dialogue function of the intelligent system.

[0125] It is evident that, for the second product related to the intelligent system, the first time can be determined based on the usage cycle of the second product. This first time is equivalent to the recommendation time of the first product. At the recommendation time of the first product, the first product is automatically recommended through the dialogue function of the intelligent system. The first product and the second product correspond to the same product category. Thus, on the one hand, the user does not need to actively provide a recommendation request, simplifying the user operation process when recommending products and improving the efficiency of product recommendation. On the other hand, the accuracy of recommending the first product is improved from both the product category and recommendation time aspects. Therefore, the effect of recommending products to users more efficiently and accurately is achieved, improving the efficiency and accuracy of product recommendation.

[0126] The electronic devices described above can implement each process of the product recommendation method described above and achieve the same effect and function, so they will not be repeated here.

[0127] Another provision provides a computer-readable storage medium for storing computer-executable instructions that, when executed by a processor, implement the following process: Receive a first message; the first message is used to recommend a first product at a first time; both the first product and the second product correspond to a first product category; the second product is related to interactive information; the interactive information includes interactive information between the user and the intelligent system; the second product has a usage period; the first time is related to the usage period. The first message is output through the dialogue function of the intelligent system.

[0128] It is evident that, for the second product related to the intelligent system, the first time can be determined based on the usage cycle of the second product. This first time is equivalent to the recommendation time of the first product. At the recommendation time of the first product, the first product is automatically recommended through the dialogue function of the intelligent system. The first product and the second product correspond to the same product category. Thus, on the one hand, the user does not need to actively provide a recommendation request, simplifying the user operation process when recommending products and improving the efficiency of product recommendation. On the other hand, the accuracy of recommending the first product is improved from both the product category and recommendation time aspects. Therefore, the effect of recommending products to users more efficiently and accurately is achieved, improving the efficiency and accuracy of product recommendation.

[0129] The computer-readable storage medium described above can implement each process of the product recommendation method described above and achieve the same effect and function, which will not be repeated here.

[0130] Another embodiment provides a computer program product comprising a computer program that, when executed by a processor, performs the following process: Receive a first message; the first message is used to recommend a first product at a first time; both the first product and the second product correspond to a first product category; the second product is related to interactive information; the interactive information includes interactive information between the user and the intelligent system; the second product has a usage period; the first time is related to the usage period. The first message is output through the dialogue function of the intelligent system.

[0131] It is evident that, for the second product related to the intelligent system, the first time can be determined based on the usage cycle of the second product. This first time is equivalent to the recommendation time of the first product. At the recommendation time of the first product, the first product is automatically recommended through the dialogue function of the intelligent system. The first product and the second product correspond to the same product category. Thus, on the one hand, the user does not need to actively provide a recommendation request, simplifying the user operation process when recommending products and improving the efficiency of product recommendation. On the other hand, the accuracy of recommending the first product is improved from both the product category and recommendation time aspects. Therefore, the effect of recommending products to users more efficiently and accurately is achieved, improving the efficiency and accuracy of product recommendation.

[0132] The computer program product described above can implement each process of the product recommendation method described above and achieve the same effect and function, so it will not be repeated here.

[0133] In the examples above, the computer-readable storage media include read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, etc.

[0134] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0135] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0136] The systems, devices, modules, or units described above can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0137] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing the above scenarios, the functions of each unit can be implemented in one or more software and / or hardware components.

[0138] Those skilled in the art will understand that one or more of the above-described embodiments can be provided as methods, systems, or computer program products. Therefore, one or more of the above-described embodiments can take the form of entirely hardware, entirely software, or a combination of software and hardware aspects. Furthermore, one or more of the above-described embodiments can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0139] The above description refers to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to the above descriptions. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0140] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0141] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0142] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0143] One or more of the above scenarios can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. One or more of the above scenarios can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0144] The above scenarios are described in a progressive manner. Similar or identical parts between scenarios can be referred to interchangeably. Each scenario focuses on its differences from the others. In particular, the system is described more simply because it is fundamentally similar to the method; relevant parts can be found in the method section.

[0145] The above description is only a partial description of this document and is not intended to limit the scope of this document. Various modifications and variations can be made to this document by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this document should be included within the scope of the claims of this document.

Claims

1. A product recommendation method, comprising: Receive the first message; The first message is used to recommend the first product at the first moment; Both the first product and the second product correspond to the first product category; The second product is related to interactive information; the interactive information includes interactive information between the user and the intelligent system; the second product has a usage period; the first time is related to the usage period; The first message is output through the dialogue function of the intelligent system.

2. The method according to claim 1, wherein the first product at least partially implements the product functions of the second product.

3. The method according to claim 2, wherein the first product and the second product are the same product in the first product category; or, the first product and the second product are different products in the first product category, and the first product and the second product have the same product attributes.

4. The method according to claim 2, wherein the quantity of the first product is multiple, and the various first products have a product combination relationship.

5. The method according to claim 1, wherein the usage period of the second product includes the usage time of the second product from the start of use to the end of use.

6. The method according to claim 5, wherein the first time is prior to the end time of use of the second product; the end time of use of the second product is related to the usage cycle of the second product.

7. The method according to claim 1, wherein the interactive information includes purchase information; and the second product includes the product purchased by the user through the intelligent system.

8. The method according to claim 1, wherein the interaction information includes dialogue messages; the intelligent system obtains product information of the second product through the dialogue messages.

9. The method according to claim 1, wherein outputting the first message through the dialogue function of the intelligent system comprises: The first message is output on the dialogue page of the intelligent system; The dialog page is used to implement the dialog function.

10. The method according to claim 1, wherein outputting the first message through the dialogue function of the intelligent system comprises: The first message is output through the voice dialogue function of the intelligent system; The first message includes voice messages; The dialogue function includes the voice dialogue function.

11. The method according to claim 1, wherein the first message is used to express a recommendation reason for the first product; If the first product and the second product are the same product in the first product category, then the recommendation reason is used to indicate that the second product is recommended before the second product is finished being used. If the first product and the second product are different products in the first product category, and the first product and the second product have the same product attributes, then the recommendation reason is used to indicate that a product with the same product attributes as the second product is recommended before the second product is finished being used. If there are multiple first products and there is a product combination relationship between each first product, then the recommendation reason is used to indicate that a product combination in the first product category is recommended before the second product is used up.

12. The method according to claim 4, wherein each of the first products is determined by the following means: Based on the second product, at least one of the first products is determined from each product corresponding to the first product category; Based on the product combination relationship, a product is selected from each product corresponding to the first product category; the selected product is used to combine with at least one first product based on the product combination relationship; each first product includes the selected product.

13. The method according to claim 12, wherein the product combination relationship includes a combination usage relationship; the step of selecting products from each product corresponding to the first product category based on the product combination relationship includes: Based on the aforementioned pairing relationship, products are selected from each product corresponding to the first product category; The selected product is intended for use in conjunction with at least one of the first products.

14. The method according to claim 12, wherein the product portfolio relationship includes a new product portfolio relationship; the step of selecting products from each product corresponding to the first product category based on the product portfolio relationship includes: Based on the new product combination relationship, products are selected from each product corresponding to the first product category; The time elapsed since the first time is less than the first duration of the selected product's release.

15. The method according to claim 12, wherein the product combination relationship includes a preferential combination relationship; the step of selecting products from each product corresponding to the first product category based on the product combination relationship includes: Based on the aforementioned discount combination relationship, products are selected from each product corresponding to the first product category; The selected product offers discounts when purchased together with at least one of the first products.

16. The method according to claim 6, wherein the first time is determined by the following means: If the first product has relevant discount information before the end time of the second product's use, the first time is determined according to the discount period of the relevant discount information; If the first product does not have relevant promotional information before the end time of the second product's use, the first time shall be determined based on the end time of the second product's use.

17. A product recommendation device, comprising: The first receiving unit is used to receive the first message; The first message is used to recommend the first product at the first moment; Both the first product and the second product correspond to a first product category; the second product is related to interactive information; the interactive information includes interactive information between the user and the intelligent system; the second product has a usage period; the first time is related to the usage period. The first output unit is used to output the first message through the dialogue function of the intelligent system.

18. An electronic device comprising: processor; as well as, A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the method described in any one of claims 1-16.

19. A computer-readable storage medium for storing computer-executable instructions that, when executed by a processor, implement the method of any one of claims 1-16.

20. A computer program product comprising a computer program that, when executed by a processor, implements the method described in any one of claims 1-16.

Images