A commodity information processing method, device, system, electronic device and storage medium

Abstract

The present application relates to a method, device, system, electronic device and storage medium for processing commodity information, the method comprising: querying a first user identifier corresponding to the user information according to the received user information; querying a user hierarchical label corresponding to the first user identifier according to the first user identifier; obtaining a second user identifier corresponding to the second user belonging to the same user hierarchical label according to the user hierarchical label; respectively querying a tree structure RFM model corresponding to the first user identifier and the second user identifier according to the first user identifier and the second user identifier; generating a tree structure RFM model according to the user identifier and the first commodity information; generating second commodity information according to the queried tree structure RFM model, and sending the second commodity information to the first user. Through the present application, the accuracy of commodity information processing is improved, and the problem of low accuracy of commodity information processing in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of data analysis, and in particular to a commodity information processing method, device, system, electronic device and storage medium. Background Art

[0002] The quality of shopping guides in traditional stores varies. Good shopping guides have a high order conversion rate, while bad shopping guides have a low order conversion rate. Shopping guides' judgment of customers basically depends on experience. How to analyze and predict customers' interested products through digital means and greatly increase customers' order rate is an urgent problem to be solved.

[0003] Some current digital technologies analyze customer transaction data and recommend products. However, current analysis methods only use customer information or product information for analysis, resulting in low accuracy in product information processing.

[0004] Currently, no effective solution has been proposed to address the problem of low accuracy in commodity information processing in related technologies. Summary of the invention

[0005] In this embodiment, a commodity information processing method, device, system, electronic device and storage medium are provided to solve the problem of low accuracy of commodity information processing in related technologies.

[0006] In a first aspect, a commodity information processing method is provided in this embodiment, and the commodity information processing method includes:

[0007] According to the received user information, query the first user identifier corresponding to the user information;

[0008] According to the first user identifier, query the user hierarchical label corresponding to the first user identifier;

[0009] According to the user hierarchical label, obtaining a second user identifier corresponding to a second user belonging to the user hierarchical label;

[0010] According to the first user identifier and the second user identifier, respectively query the tree structure RFM model corresponding to the first user identifier and the second user identifier; the tree structure RFM model is generated according to the user identifier and the first commodity information;

[0011] Generate second product information based on the queried tree structure RFM model, and send the second product information to the first user.

[0012] In some of the embodiments, the root node of the tree structure RFM model is a user identification node, the child nodes of the tree structure RFM model are product category nodes of the product, and the leaf nodes of the tree structure RFM model are product name nodes.

[0013] In some of the embodiments, generating the second product information according to the queried tree structure RFM model includes:

[0014] Obtain the RFM value of the leaf node of the queried tree structure RFM model, calculate the RFM value of the child node according to the RFM value of the leaf node, and generate the second product information according to the RFM value of the leaf node and the RFM value of the child node.

[0015] In some embodiments, the RFM value of the child node is calculated according to the RFM value of the leaf node, and the second product information is generated according to the RFM value of the leaf node and the RFM value of the child node, including:

[0016] Sort the commodity categories corresponding to the subnodes according to the RFM values ​​of the subnodes, and select a commodity category whose commodity category sorting satisfies a first preset condition as a first commodity category;

[0017] Sort the product names under the first product category according to the RFM value of the leaf node, and select the product name whose product name sorting meets the second preset condition as the first product name;

[0018] The second product information is generated according to the first product category and the first product name.

[0019] In some of the embodiments, the user stratification label is generated based on the user's RFM value, and the user's RFM value is generated based on the user's transaction time interval, the user's transaction number and the user's transaction amount.

[0020] In some of the embodiments, the RFM value of the leaf node is generated according to the commodity transaction time interval, the commodity transaction number and the commodity transaction amount.

[0021] In a second aspect, a commodity information processing device is provided in this embodiment, and the commodity information processing device includes:

[0022] A first query module, configured to query a first user identifier corresponding to the user information according to the received user information;

[0023] A second query module, configured to query a user hierarchical label corresponding to the first user identifier according to the first user identifier;

[0024] An acquisition module, configured to acquire, according to the user hierarchical label, a second user identifier corresponding to the second user under the user hierarchical label;

[0025] A third query module is used to query the tree structure RFM model corresponding to the first user identifier and the second user identifier respectively according to the first user identifier and the second user identifier; the tree structure RFM model is generated according to the user identifier and the first commodity information;

[0026] A processing module is used to generate second product information according to the queried tree structure RFM model, and send the second product information to the first user.

[0027] In a third aspect, a commodity information processing system is provided in this embodiment, and the commodity information processing system includes a shopping guide device and a cloud server;

[0028] The shopping guide device is used to receive user information, send the user information to the cloud server, and receive second product information sent by the cloud server;

[0029] The cloud server is used to execute the commodity information processing method described in any one of the first aspects.

[0030] In a fourth aspect, an electronic device is provided in this embodiment, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the commodity information processing method described in the first aspect.

[0031] In a fifth aspect, in this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the commodity information processing method described in the first aspect are implemented.

[0032] Compared with the related art, the product information processing method, device, system, electronic device and storage medium provided in this embodiment obtain all second users under the same user hierarchical label as the first user according to the user identification of the first user, and generate second product information including product recommendation information according to the tree structure RFM model corresponding to the first user and the second user, and display the information to the user through the shopping guide device. This embodiment uses user information and product information for information processing and analysis, improves the accuracy of product information processing, and solves the problem of low accuracy of product information processing in the prior art.

[0033] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0035] Figure 1 is a hardware structure block diagram of a terminal for executing a commodity information processing method of this embodiment;

[0036] Figure 2 is a structural diagram of a commodity information processing system of this embodiment;

[0037] Figure 3 is a flow chart of a commodity information processing method of this embodiment;

[0038] Figure 4 is a structural diagram of a tree structure RFM model of this embodiment;

[0039] Figure 5 is a flow chart of a commodity information processing method of the preferred embodiment;

[0040] Figure 6 It is a structural block diagram of a commodity information processing device of this embodiment. DETAILED DESCRIPTION

[0041] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0042] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the", "these" and the like in this application do not represent quantitative restrictions, and they can be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether directly or indirectly. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. Usually, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0043] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 is a hardware structure block diagram of a terminal for executing a commodity information processing method of this embodiment. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) processor 102 and memory 104 for storing data, wherein processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0044] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as a computer program corresponding to a commodity information processing method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0045] The transmission device 106 is used to receive or send data via a network. The above network includes a wireless network provided by the communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0046] In this embodiment, a commodity information processing system is provided. Figure 2 is a structural diagram of a commodity information processing system of this embodiment. Figure 2 As shown, the commodity information processing system includes a shopping guide device 210 and a cloud server 220.

[0047] The shopping guide device 210 is used to receive user information, send the user information to the cloud server 220, and receive the second product information sent by the cloud server.

[0048] Specifically, the shopping guide device 210 may be an all-in-one device having a display screen and a computer host, and the shopping guide device 210 may display product information to the user through the display screen. Exemplarily, the product information may be a product name or a product category. The display screen also has an input function, and the user may input user information through the display screen. Exemplarily, the user information may be a user's mobile phone number. In addition, the shopping guide device 210 also has a camera device, and the shopping guide device 210 obtains the user information of the user through the camera device. Exemplarily, the user information may be the user's facial information. The shopping guide device 210 sends the obtained user information to the cloud server 220, and receives the second product information sent by the cloud server 220.

[0049] The cloud server 220 is used to execute a commodity information processing method provided in any of the following embodiments.

[0050] In this embodiment, a commodity information processing method is provided. Figure 3 is a flow chart of a commodity information processing method of this embodiment. Figure 2 and Figure 3 As shown, the process includes the following steps:

[0051] Step S310: query the first user identifier corresponding to the user information according to the received user information.

[0052] Specifically, after receiving the user information sent by the shopping guide device 210, the cloud server 220 queries the first user identifier corresponding to the user information according to the user information. The first user identifier is a unique identifier corresponding to the user, and the user identifier corresponding to each user is different and unique. Exemplarily, the user information can be user information that can represent the user's identity, such as the user's mobile phone number and the user's facial information.

[0053] Step S320: query the user hierarchical label corresponding to the first user identifier according to the first user identifier.

[0054] Specifically, the cloud server 220 queries the user stratification label corresponding to the first user identifier according to the first user identifier obtained in step S310. Specifically, the cloud server 220 can generate a user stratification label corresponding to the user according to the user's RFM (Recency, Frequency, Money) value, and store the user stratification label corresponding to the user identifier in the memory. Among them, the user identifier of each user corresponds to a user stratification label, and each user stratification label can correspond to multiple user identifiers. Users under the same user stratification label have the same or similar transaction habits, product preferences, etc. The user's RFM value here can be generated according to the user's transaction time interval, the user's transaction number and the user's transaction amount.

[0055] Step S330: acquiring, according to the user hierarchical tag, a second user identifier corresponding to a second user belonging to the same user hierarchical tag.

[0056] Among them, the above-mentioned second user can be all other users or some users who belong to the same user hierarchy label as the first user. For example, the user hierarchy label of the first user is an important value user, and the users under this user hierarchy label have the same or similar transaction habits, product preferences, etc., and all other users or some users under this user hierarchy label are obtained, and their product information is also pushed to the first user, thereby improving the accuracy of product recommendations. Specifically, the cloud server 220 queries the memory for the second user identifier corresponding to all the second users belonging to the same user hierarchy label according to the user hierarchy label obtained by querying in step S320. The first user and the second user corresponding to the first user identifier belong to the same user hierarchy label.

[0057] Step S340: query the tree structure RFM model corresponding to the first user identifier and the second user identifier respectively according to the first user identifier and the second user identifier; the tree structure RFM model is generated according to the user identifier and the first product information.

[0058] Specifically, the cloud server 220 queries the tree structure RFM model corresponding to the first user identifier and the second user identifier respectively according to the first user identifier obtained in step S310 and the second user identifier corresponding to all the second users belonging to the same user layer label queried in step S330. The tree structure RFM model is generated by the cloud server 220 according to the user identifier and the product information, that is, the cloud server 220 generates a corresponding tree structure RFM model for each user. Exemplarily, the product information includes information such as the product category associated with the user, the product name, and the RFM value of the product corresponding to the product name. Among them, each product category may include multiple product names, and the RFM value of the product is generated based on the transaction time interval of the product, the number of transactions of the product, and the transaction amount of the product.

[0059] Step S350: Generate second product information according to the queried tree structure RFM model, and send the second product information to the first user.

[0060] Specifically, the cloud server 220 queries the tree structure RFM model corresponding to the first user and the second user according to step S340, generates the second product information, and sends the second product information to the first user. The cloud server 220 calculates the RFM value of the product category corresponding to the product category based on the queried tree structure RFM model and the RFM value of the product corresponding to the product name, and generates the second product information based on the RFM value of the product category and the RFM value of the product. Exemplarily, the RFM values ​​of the product categories can be sorted, the product categories corresponding to the RFM values ​​of the top N product categories are taken, the product names under the top N product categories are sorted according to the RFM values ​​of the products corresponding to the product names, the product names corresponding to the RFM values ​​of the top M products are taken, and the top N product categories and the top M product names are sent to the first user as the second product information to implement product recommendations to the first user.

[0061] In this embodiment, the cloud server 220 obtains all second users under the same user hierarchical label as the first user according to the user ID of the first user, generates second product information including product recommendation information according to the tree structure RFM model corresponding to the first user and the second user, and displays the information to the user through the shopping guide device 210. This embodiment uses user information and product information for information processing and analysis, improves the accuracy of product information processing, and solves the problem of low accuracy of product information processing in the prior art.

[0062] In some embodiments, a tree structure RFM model is provided. Figure 4 is a structural diagram of a tree structure RFM model of this embodiment, such as Figure 4 As shown, the tree structure RFM model includes a root node, child nodes and leaf nodes. The root node of the tree structure RFM model is a user identification node 410 , the child nodes of the tree structure RFM model are product category nodes 420 , and the leaf nodes of the tree structure RFM model are product name nodes 430 .

[0063] In some of the embodiments, second product information is generated based on the queried tree structure RFM model, including: the cloud server 220 obtains the RFM value of the leaf node of the queried tree structure RFM model, calculates the RFM value of the child node based on the RFM value of the leaf node, and generates the second product information based on the RFM value of the leaf node and the RFM value of the child node.

[0064] In some of the embodiments, the RFM value of the child node is calculated according to the RFM value of the leaf node, and the second product information is generated according to the RFM value of the leaf node and the RFM value of the child node, including: the cloud server 220 sorts the product categories corresponding to the child nodes according to the RFM value of the child nodes, and selects the product categories whose product category sorting meets the first preset condition as the first product category. The cloud server 220 sorts the product names under the first product category according to the RFM value of the leaf node, and selects the product names whose product name sorting meets the second preset condition as the first product name. The second product information is generated according to the first product category and the first product name. Among them, selecting the product category whose product category sorting meets the first preset condition as the first product category can be to select the product category with the first N positions in the product category sorting as the first product category; selecting the product name whose product name sorting meets the second preset condition as the first product name can be to select the product name with the first M positions in the product name sorting as the first product name.

[0065] The present embodiment is described and illustrated below through preferred embodiments.

[0066] Figure 5 is a flow chart of a commodity information processing method of this preferred embodiment, such as Figure 2 and Figure 5 As shown, the commodity information processing method includes the following steps:

[0067] Step S501, the shopping guide device 210 obtains the user's facial information through the camera, the shopping guide device 210 requests the cloud server 220 to perform facial recognition on the user, and the cloud server 220 returns a unique user ID to confirm the user.

[0068] Step S502, the shopping guide device 210 communicates with the cloud server 220 via the user ID and searches for the constructed user model.

[0069] Specifically, the shopping guide device 210 communicates with the cloud server 220 through the user's unique user ID, and searches the cloud server 220 for the user model that has been constructed.

[0070] The process of building a user model is as follows:

[0071] The cloud server 220 constructs a user model ModelA based on the user's transaction data. The user model is an RFM model, and the model is as follows:

[0072] The R (Recency) value is the time interval between the user's most recent transaction. The score is calculated based on the date of the most recent transaction. The closer the date is to the current date, the higher the score. The F (Frequency) value is the number of transactions the user has made in the recent period. The score is calculated based on the transaction frequency. The higher the transaction frequency, the higher the score. The M (Monetray) value is the transaction amount of the user in the recent period. The score is calculated based on the transaction amount. The higher the transaction amount, the higher the score.

[0073] The R value, F value and M value are weighted to obtain the user's RFM value. Here, different weight coefficients can be assigned to the R value, F value and M value. Users are stratified according to their RFM values. The stratification labels of users are described in Table 1. Here, users are divided into 8 categories, corresponding to 8 stratification labels.

[0074] Table 1 Hierarchical labels of users

[0075]

[0076] The thresholds of time interval, number of transactions, and transaction amount are initially based on industry experience. After the users are stratified, the system automatically readjusts the thresholds of time interval, number of transactions, and transaction amount according to the 80 / 20 principle to make them closer to the 80 / 20 principle classification, and finally obtains the stratified labels of the users.

[0077] Step S503: the shopping guide device 210 queries the user IDs of all other users under the hierarchical label corresponding to the user ID according to the user model.

[0078] Step S504: the cloud server 220 constructs a tree structure model of users and commodities.

[0079] The cloud server 220 constructs a tree structure model ModelB of users and commodities. The root node of the tree is the user node, and the root node information includes the user ID. The child node is the category of the commodity, and the leaf node is the RFM model calculation score of the commodity. The weighted path of the tree is calculated as follows: the weight of the weighted path of the leaf node is the RFM model calculation score of the commodity, and the weight of the weighted path of the child node is the sum of all leaf nodes under the child node.

[0080] The R (Recency) value is the time interval between the last transaction of the product within a certain period. The score is calculated based on the date of the last transaction. The closer to the current date, the higher the score. The F (Frequency) value is the number of times the product has been traded within a certain period. The score is calculated based on the transaction frequency. The higher the transaction frequency, the higher the score. The M (Monetray) value is the amount of money traded for the product within a certain period. The score is calculated based on the transaction amount. The higher the transaction amount, the higher the score.

[0081] For example, a certain period is customized by the store and is set to T (based on days), such as one year (365 days), and the score is based on 100 points. ((Current time - the time of the last transaction) rounded to days) = X days, then R value = 100 × (1-X / T); the number of transactions of all commodities within a certain period is M, the score is based on 100 points, the number of transactions of the current commodity is N, then F value = 100 × N / M; the total transaction amount of commodities within a certain period is K, the score is based on 100 points, the transaction amount of the current commodity is P, then M value = 100 × P / K. Weighted processing is performed on the R value, F value and M value to obtain the RFM value of the leaf node. Here, different weighting coefficients can be assigned to the R value, F value and M value. The RFM value is the weight of the weighted path of the leaf node, and the leaf nodes are sorted according to the RFM value. The weight of the weighted path of a product category is the sum of all leaf nodes under the product category, and the product categories are sorted according to the weight of the weighted path of the product category.

[0082] In step S505 , the cloud server 220 finds the top-ranked product category and the top-ranked products under the product category corresponding to the tree structure model of the user and the product according to the unique ID of the user.

[0083] In step S506, the cloud server 220 searches for top-ranked product categories of other users belonging to the same hierarchical tag and top-ranked products under the product category according to the hierarchical tag of the user.

[0084] Step S507: the product sets found in step S505 and step S506 are sorted according to the RFM scores to give a final product recommendation ranking.

[0085] Step S508 , the cloud server 220 returns the product recommendation ranking to the shopping guide device 210 .

[0086] The shopping guide device displays the introduction, price and other video, graphic and text descriptions of these products on the large screen. Users can directly place orders for these products based on the large screen of the shopping guide device to complete consumption conversion. The user's order data is also included in the dynamic calculation of Model A and Model B.

[0087] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0088] In this embodiment, a commodity information processing device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. The terms "module", "unit", "subunit", etc. used below can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0089] Figure 6 is a structural block diagram of a commodity information processing device of this embodiment, such as Figure 6 As shown, the device comprises:

[0090] A first query module 610, configured to query a first user identifier corresponding to the user information according to the received user information;

[0091] The second query module 620 is used to query the user hierarchical label corresponding to the first user identifier according to the first user identifier;

[0092] An acquisition module 630 is used to acquire, according to the user hierarchical label, a second user identifier corresponding to the second user under the user hierarchical label;

[0093] The third query module 640 is used to query the tree structure RFM model corresponding to the first user identifier and the second user identifier respectively according to the first user identifier and the second user identifier; the tree structure RFM model is generated according to the user identifier and the first commodity information;

[0094] The processing module 650 is used to generate second product information according to the queried tree structure RFM model, and send the second product information to the first user.

[0095] In this embodiment, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0096] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0097] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0098] S1, querying a first user identifier corresponding to the user information according to the received user information;

[0099] S2, according to the first user identifier, querying the user hierarchical label corresponding to the first user identifier;

[0100] S3, according to the user hierarchical label, obtaining a second user identifier corresponding to a second user belonging to the same user hierarchical label;

[0101] S4, querying the tree structure RFM model corresponding to the first user identifier and the second user identifier respectively according to the first user identifier and the second user identifier; the tree structure RFM model is generated according to the user identifier and the first product information;

[0102] S5, generating second product information according to the queried tree structure RFM model, and sending the second product information to the first user.

[0103] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and will not be repeated in this embodiment.

[0104] In addition, in combination with a commodity information processing method provided in the above embodiment, a storage medium can also be provided in this embodiment to implement the method. The storage medium stores a computer program; when the computer program is executed by a processor, the steps of any commodity information processing method in the above embodiment are implemented.

[0105] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0106] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

[0107] The term "embodiment" in this application refers to a specific feature, structure or characteristic described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various locations in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. It is clearly or implicitly understood by those of ordinary skill in the art that the embodiments described in this application can be combined with other embodiments without conflict.

[0108] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A commodity information processing method, characterized in that: The commodity information processing method comprises: According to the received user information, query the first user identifier corresponding to the user information; According to the first user identifier, query the user hierarchical label corresponding to the first user identifier; According to the user hierarchical label, obtaining a second user identifier corresponding to a second user belonging to the user hierarchical label; According to the first user identifier and the second user identifier, the tree structure RFM model corresponding to the first user identifier and the second user identifier is queried respectively; the tree structure RFM model is generated according to the user identifier and the first commodity information; the root node of the tree structure RFM model is the user identifier node, the child nodes of the tree structure RFM model are the commodity category nodes of the commodity, and the leaf nodes of the tree structure RFM model are the commodity name nodes; the first commodity information includes the commodity category and commodity name associated with the user and the RFM value information of the commodity corresponding to the commodity name; Generate second product information according to the queried tree structure RFM model, and send the second product information to the first user; The generating the second product information according to the queried tree structure RFM model includes: Sort the commodity categories corresponding to the subnodes according to the RFM values ​​of the subnodes, and select a commodity category whose commodity category sorting satisfies a first preset condition as a first commodity category; Sort the product names under the first product category according to the RFM value of the leaf node, and select the product name whose product name sorting meets the second preset condition as the first product name; The second product information is generated according to the first product category and the first product name.

2. The commodity information processing method according to claim 1, characterized in that: The step of generating second product information according to the queried tree structure RFM model further includes: Obtain the RFM value of the leaf node of the queried tree structure RFM model, calculate the RFM value of the child node according to the RFM value of the leaf node, and generate the second product information according to the RFM value of the leaf node and the RFM value of the child node.

3. The commodity information processing method according to any one of claims 1 to 2, characterized in that: The user stratification label is generated according to the user's RFM value, and the user's RFM value is generated according to the user's transaction time interval, the user's transaction times and the user's transaction amount.

4. The commodity information processing method according to any one of claims 1 to 2, characterized in that: The RFM value of the leaf node is generated according to the commodity transaction time interval, the commodity transaction number and the commodity transaction amount.

5. A commodity information processing device, characterized in that: The commodity information processing device comprises: A first query module, configured to query a first user identifier corresponding to the user information according to the received user information; A second query module, configured to query a user hierarchical label corresponding to the first user identifier according to the first user identifier; An acquisition module, configured to acquire, according to the user hierarchical label, a second user identifier corresponding to the second user under the user hierarchical label; A third query module is used to query the tree structure RFM model corresponding to the first user identifier and the second user identifier respectively according to the first user identifier and the second user identifier; the tree structure RFM model is generated according to the user identifier and the first commodity information; the root node of the tree structure RFM model is the user identifier node, the child nodes of the tree structure RFM model are the commodity category nodes of the commodity, and the leaf nodes of the tree structure RFM model are the commodity name nodes; the first commodity information includes the commodity category and commodity name associated with the user and the RFM value information of the commodity corresponding to the commodity name; A processing module, configured to generate second product information according to the queried tree structure RFM model, and send the second product information to the first user; The generating the second product information according to the queried tree structure RFM model includes: Sort the commodity categories corresponding to the subnodes according to the RFM values ​​of the subnodes, and select a commodity category whose commodity category sorting satisfies a first preset condition as a first commodity category; Sort the product names under the first product category according to the RFM value of the leaf node, and select the product name whose product name sorting meets the second preset condition as the first product name; The second product information is generated according to the first product category and the first product name.

6. A commodity information processing system, characterized in that: The commodity information processing system includes a shopping guide device and a cloud server; The shopping guide device is used to receive user information, send the user information to the cloud server, and receive second product information sent by the cloud server; The cloud server is used to execute the commodity information processing method according to any one of claims 1 to 4.

7. An electronic device comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor is configured to run the computer program to execute the commodity information processing method according to any one of claims 1 to 4.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the product information processing method according to any one of claims 1 to 4 are implemented.

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