Method and device for recommending shopping route

Method and device for recommending shopping routes

Technical field

[0001] The present invention relates to the field of shopping carts, and in particular, to a method and apparatus for recommending a shopping route.

Background technique

[0002] With the development of the Internet industry, online shopping has been widely accepted by people and traditional shopping methods have encountered challenges, but traditional shopping methods are still an integral part of people's lives. In relatively large shopping malls, products There are many kinds of products that consumers need to purchase are often distributed in various areas or corners of supermarkets. Consumers waste a lot of time in searching for goods, how to help consumers quickly complete the whole process of shopping, increase purchase speed, and increase consumer shopping. Experience has become a technical problem that needs to be solved.

[0003] For the technical problems in the related art that cannot intelligently guide users to complete the shopping process quickly, no effective solution has been proposed yet.

Summary of the Invention

[0004] The embodiments of the present invention provide a method and an apparatus for recommending a shopping route to at least solve a technical problem in a related art that cannot intelligently guide a user to quickly complete a shopping process.

According to an aspect of an embodiment of the present invention, a method for recommending a shopping route is provided. The method includes: acquiring a shopping requirement information of a target user; and inputting shopping demand information into a pre-trained neural network model to determine At least one recommended commodity in the target mall; recommending a shopping route to the target user based on the location of the at least one recommended commodity in the target mall.

[0006] Further, the shopping demand information includes at least one of the following: a shopping demand list including at least one item that the target user desires to purchase; a shopping demand category including at least one product type that the target user desires to purchase; shopping preference label , used to indicate the target user's shopping preferences.

[0007] Further, acquiring the target user's shopping requirement information includes: obtaining the target user authorized access authority, wherein the access authority is used to allow obtaining the shopping requirement information; and the shopping requirement information is input into the pre-trained neural network model to determine the target. At least one recommended commodity in the shopping mall includes: inputting the shopping demand information into a neural network model; determining at least one recommended commodity in the commodity database of the target mall through a neural network model, wherein at least one recommended commodity is in the shopping demand list At least one item of merchandise, or at least one merchandise item type, or at least one merchandise type, or a product associated with a shopping preference feature.

[0008] Further, recommending the shopping route to the target user according to the position of the at least one recommended product in the target mall includes prompting the target user of at least one recommended commodity and receiving the commodity selected by the target user from at least one recommended commodity. The current position of the target user and the position of the target user's selected product in the target mall are acquired; the shopping route is recommended to the target user according to the target user's current position and the position of the target user's selected commodity in the target mall.

[0009] Further, the recommendation of the shopping route to the target user according to the current position of the target user and the position of the target product selected in the target shopping mall includes: determining at least one shopping route, wherein each shopping route in the at least one shopping route is The arrangement order of the commodity locations is different; at least one shopping route is suggested to the target user; the shopping route selected by the target user in at least one shopping route is received; and the target user is navigated according to the shopping route.

[0010] Further, in the case that the shopping demand information is empty, the method further includes prompting the product area information in the target shopping mall through the air-conditioning equipment in the target shopping mall, wherein the product area information includes the product type in the target shopping mall and The location of each type of product.

[0011] According to another aspect of the embodiments of the present invention, there is further provided an apparatus for recommending a shopping route, the apparatus comprising: an obtaining unit for acquiring a target user's shopping requirement information; a determining unit for applying shopping The demand information is input into the pre-trained neural network model to determine at least one recommended commodity in the target shopping mall; and the first prompting unit is configured to recommend the shopping route to the target user according to the position of the at least one recommended commodity in the target mall.

[0012] Further, the shopping demand information includes at least one of the following: a shopping demand list including at least one item that the target user desires to purchase; a shopping demand category including at least one product type that the target user desires to purchase; shopping preference label , used to indicate the target user's shopping preferences.

[0013] Further, the acquiring unit is further configured to acquire the access authority authorized by the target user, wherein the access authority is used to allow acquiring the shopping requirement information; the determining unit is further configured to input the shopping requirement information into the neural network model and pass the neural network model. Determining at least one recommended commodity in a commodity database of the target mall, wherein at least one recommended commodity is a commodity in at least one commodity in the list of shopping needs, or an commodity in at least one commodity type, or at least one The product associated with the product type or the product associated with the shopping preference feature.

[0014] Further, the first prompting unit includes: a prompting module configured to prompt the target user with at least one recommended product; a receiving module configured to receive the product selected by the target user from the at least one recommended product; In order to obtain the target user's current position and the position of the target user's selected product in the target mall; a prompting module for recommending the shopping route to the target user according to the target user's current position and the position of the target user's selected commodity in the target mall.

[0015] Further, the prompting module comprises: a determining sub-module for determining at least one shopping route, wherein the ordering of the commodity positions of each shopping route in at least one shopping route is different; the prompting sub-module is configured to provide the target user The at least one shopping route is prompted; the receiving sub-module is configured to receive the shopping route selected by the target user in the at least one shopping route; and the navigation sub-module is configured to navigate the target user according to the shopping route.

[0016] Further, in the case that the shopping requirement information is empty, the apparatus further includes a second prompting unit for prompting the product area information in the target shopping mall through the air-conditioning equipment in the target shopping mall, wherein the commodity area information includes The type of merchandise in the target mall and the location of each type of merchandise.

[0017] According to another aspect of the embodiments of the present invention, a storage medium is further provided. The storage medium includes a stored program, and a device where the storage medium is located during execution of the program executes the method for recommending a shopping route of the present invention. method.

[0018] According to another aspect of the embodiments of the present invention, a processor is further provided for executing a program, wherein the program runs a method for recommending a shopping route of the present invention.

[0019] In the embodiment of the present invention, by acquiring the shopping requirement information of the target user, the shopping demand information is input into the pre-trained neural network model to determine at least one recommended commodity in the target shopping mall; according to at least one recommended commodity The location in the target shopping mall recommends the shopping route to the target user, solves the technical problem in the related art that cannot intelligently guide the user to complete the shopping process quickly, and further realizes the technical effect that can improve the user's shopping experience in the shopping mall.

Description of the drawings

The drawings described herein are provided to provide a further understanding of the present invention and constitute a part of the present application. The exemplary embodiments of the present invention and descriptions thereof are used to explain the present invention and do not constitute improper limitations to the present invention. In the drawing:

[0021] FIG. 1 is a flowchart of an alternative method for recommending a shopping route according to an embodiment of the present invention;

[0022] FIG. 2 is a schematic diagram of an optional apparatus for recommending a shopping route according to an embodiment of the present invention.

detailed description

To enable those skilled in the art to better understand the solutions of the present invention, the following clearly describes the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described The embodiments are merely a part of the embodiments of the present invention and not all the embodiments. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0024] It should be noted that the terms “first”, “second”, and the like in the description and claims of the present invention and the foregoing drawings are used to distinguish similar objects and do not have to be used to describe a specific sequence or Priorities. It should be understood that the data used as such may be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in other than the order illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that comprises a series of steps or units need not be limited to a clear listing Those steps or units may instead include other steps or units not explicitly listed or inherent to these processes, methods, products or devices.

[0025] The present application provides an embodiment of a method for recommending a shopping route. It should be noted that an execution body of the method provided in this embodiment may be a processor, and the processor may be disposed in an air conditioner or other electronic device.

[0026] FIG. 1 is a flowchart of an optional method for recommending a shopping route according to an embodiment of the present invention. As shown in FIG. 1, the method includes the following steps:

[0027] step S101, obtaining the target user's shopping requirement information;

[0028] step S102, the shopping demand information is input into the pre-trained neural network model to determine at least one recommended commodity in the target shopping mall;

[0029] Step S103: recommend a shopping route to a target user according to a position of the at least one recommended product in the target mall.

[0030] For example, a user may input his own shopping demand information on a terminal provided in a shopping mall, and the shopping demand information may be a determined one kind of product, or may be a certain kind of product type, or may be any user-provided favorite tag or the like. Information indicating the shopping needs of the target user. Specifically, the shopping requirement information may include at least one of the following: a list of shopping needs, including at least one item that the target user desires to purchase; a category of shopping requirements including at least one product type that the target user desires to purchase; a shopping preference tag, Used to indicate the target user's shopping preferences.

[0031] Optionally, when acquiring the shopping requirement information of the target user, it may also be acquired through a communication method, for example, the target user authorizes the access permission through a terminal (for example, a mobile terminal) logging in an application or entering an authorization code, and the like. Obtaining the access authority enables the execution subject executing the method provided by the embodiment to acquire the target user's shopping demand list, where the shopping demand list includes at least one item that the target user desires to purchase.

[0032] Specifically, when the target user's shopping requirement information is obtained through the communication method, first, the target user is authorized to obtain the access permission, wherein the access permission is used to allow the acquisition of the shopping requirement information, and then the shopping requirement information is input into the neural network. The model determines at least one recommended commodity in a commodity database of a target mall through a neural network model, wherein at least one recommended commodity is a commodity in at least one commodity in the shopping requirement list or at least one commodity type , or an item associated with at least one item type, or an item associated with a shopping preference feature. It should be noted that at least one of the recommended products must be a stocked product in the target presence database.

[0033] When the shopping route is recommended to the target user according to the position of the at least one recommended product in the target mall, the target user may be prompted with at least one recommended product. The prompt may be the display screen of the mobile terminal sent to the target user. In the above, after presenting the recommended product to the target user, the target user may make a selection therein, and the result of the selection will be fed back to the subject performing the method provided in the embodiment.

[0034] After receiving the target user's selected product in the at least one recommended product, the current position of the target user and the position of the target user's selected product in the target market are acquired, and the target user selects according to the current position of the target user and the target user. The product is recommended to the target user at the location in the target mall. Specifically, the shopping route can be prompted through the target user's mobile terminal or a supporting display device in the target shopping mall, and the shopping route is marked with the route in the map of the target shopping mall.

[0035] When recommending a shopping route, since the target user may select more than one product, multiple shopping routes may be generated and recommended to the target user according to the difference in the order of arrival. The order of arrival of the product positions in each shopping line is different. After at least one shopping route is prompted to the target user, the shopping route selected by the target user in the at least one shopping route is received, and the target user is navigated according to the shopping route. Specifically, when the user is navigated according to the shopping route, the current position of the target user may be displayed through the terminal device of the target user. Optionally, the current position of the target user may also be prompted in conjunction with the supporting equipment in the target shopping mall. For example, whether the target user passes through the air conditioning device is detected, and if so, the current location and the next route direction are reported, or indicated by the route indicator set on the ground.

[0036] Further, in the case that the shopping demand information is empty, the commodity area information in the target shopping mall is also prompted through the air-conditioning equipment in the target shopping mall, wherein the commodity area information includes the commodity types in the target shopping mall and each type of The corresponding position of the product.

[0037] For example, in an application scenario of the method provided in this embodiment, after a user holding a mobile terminal enters a shopping mall, the air-conditioning device in the shopping mall can obtain the shopping within the shopping app within the user's mobile terminal. The items in the car, and determine the items that the user may purchase in the shopping mall according to the items in the shopping cart, determine the specific location of the products in the shopping mall, and provide the shopping route for the user. If there is no product in the user's shopping cart, the air conditioner displays the product type in each floor of the shopping mall to the user. After the user clicks the product type on the mobile terminal, the user is automatically provided with the location of the product. [0038] The embodiment obtains the target user's shopping requirement information; inputs the shopping requirement information into a pre-trained neural network model to determine at least one recommended commodity in the target mall; according to at least one recommended commodity in the target mall The location recommends the shopping route to the target user, solves the technical problem in the related art that cannot intelligently guide the user to complete the shopping process quickly, and further realizes a technical effect that can improve the user's shopping experience in the shopping mall.

[0039] It should be noted that while the flowcharts of the drawings illustrate the logical sequence, in some cases, the illustrated or described steps may be performed in an order other than that herein.

[0040] The present application further provides an embodiment of a storage medium. The storage medium of this embodiment includes a stored program, wherein a device where the storage medium is controlled during execution of the program performs the method for recommending a shopping route according to an embodiment of the present invention. method.

[0041] The present application further provides an embodiment of a processor. The processor of this embodiment is used to run a program, and the method for recommending a shopping route according to an embodiment of the present invention is executed when the program runs.

[0042] The present application also provides an embodiment of a device for recommending a shopping route.

FIG. 2 is a schematic diagram of an apparatus for recommending a shopping route according to an embodiment of the present invention. As shown in FIG. 2, the apparatus includes an obtaining unit 10, a determining unit 20, and a first prompting unit 3. , Wherein, the obtaining unit 10 is configured to acquire the target user's shopping demand information; the determining unit 20 is configured to input the shopping demand information into a pre-trained neural network model to determine at least one recommended commodity in the target shopping mall; the first prompt unit 3 〇 is used to recommend a shopping route to a target user based on the location of at least one of the recommended products in the target mall. _

[0044] In this embodiment, the acquisition unit acquires the target user's shopping requirement information, and the determination unit inputs the shopping requirement information into the pre-trained neural network model to determine at least one recommended commodity in the target mall according to the first prompt unit. At least one recommended commodity recommends a shopping route to a target user at a location in a target shopping mall, solving a technical problem in related technologies that cannot intelligently guide the user to complete the shopping process quickly, thereby realizing the improvement of the user's shopping experience in the shopping mall. Technical effect.

[0045] Further, the shopping demand information includes at least one of the following: a shopping demand list including at least one item that the target user desires to purchase; a shopping demand category including at least one product type that the target user desires to purchase; shopping preference label , used to indicate the target user's shopping preferences.

[0046] Further, the acquiring unit is further configured to acquire the access authority authorized by the target user, wherein the access authority is used to allow obtaining the shopping requirement information; the determining unit is further configured to input the shopping requirement information into the neural network model and pass through the neural network model. Determining at least one recommended commodity in a commodity database of the target mall, wherein at least one recommended commodity is a commodity in at least one commodity in the list of shopping needs, or an commodity in at least one commodity type, or at least one The product associated with the product type or the product associated with the shopping preference feature.

[0047] Further, the first prompting unit comprises: a prompting module for prompting the target user with at least one recommended product; a receiving module for receiving the target user's selected product in the at least one recommended product; In order to obtain the target user's current position and the position of the target user's selected product in the target mall; a prompting module for recommending the shopping route to the target user according to the target user's current position and the position of the target user's selected commodity in the target mall.

[0048] Further, the prompting module comprises: a determining sub-module for determining at least one shopping route, wherein the ordering of the commodity positions of each shopping route in the at least one shopping route is different; the prompting sub-module is configured to provide the target user The at least one shopping route is prompted; the receiving sub-module is configured to receive the shopping route selected by the target user in the at least one shopping route; and the navigation sub-module is configured to navigate the target user according to the shopping route.

[0049] Further, in the case that the shopping requirement information is empty, the apparatus further includes a second prompting unit for prompting the product area information in the target shopping mall through the air-conditioning equipment in the target shopping mall, wherein the commodity area information includes The type of merchandise in the target mall and the location of each type of merchandise.

[0050] The above apparatus may include a processor and a memory, and the above units may all be stored as a program unit in a memory. The processor executes the above program unit stored in the memory to implement corresponding functions.

The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM), and/or non-volatile memory, such as read only memory (ROM) or flash memory (flash RAM), and memory. Including at least one memory chip.

[0052] The above order of the embodiments of the present application does not represent the advantages or disadvantages of the embodiments.

[0053] In the foregoing embodiments of the present application, the description of each embodiment has its own emphasis. For the part that is not described in detail in an embodiment, reference may be made to the relevant description of other embodiments. In the several embodiments provided by the present application, it should be understood that the disclosed technical content may be implemented in other manners.

[0054] The device embodiments described above are merely illustrative. For example, the division of the units may be a logical function division. In actual implementation, there may be another division manner. For example, multiple units or components may be The combination can be integrated into another system, or some features can be ignored or not performed. In addition, the illustrated or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, units or modules, and may be electrical or other forms.

[0055] In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The above integrated unit can be implemented either in hardware or in software.

[0056] The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the part of the technical solution of the present application or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium. The instructions include instructions for enabling a computer device (which may be a personal computer, a server, a network device, or the like) to perform all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes various media that can store program codes, such as a U disk, a read-only memory (ROM), a Read-Only Memory (NROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk. .

The above description is only a preferred embodiment of the present application. It should be pointed out that for those skilled in the art, a number of improvements and improvements can be made without departing from the principle of the present application. These improvements and retouches should also be deemed as the scope of protection of this application.