CN112785374B - Information recommendation system and method based on unmanned retail terminal - Google Patents
Information recommendation system and method based on unmanned retail terminal Download PDFInfo
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Abstract
The invention relates to the technical field of information recommendation systems, in particular to an information recommendation system and method based on an unmanned retail terminal. When the customer purchases the commodity, the invention can provide more related, similar and matched products for the customer before and after purchasing, and can pay through WeChat, Paibao and credit card, and the payment module can income and store the information of the customer in the payment process, so as to push the commodity information to the customer.
Description
Technical Field
The invention relates to an information recommendation system and method, in particular to an information recommendation system and method based on an unmanned retail terminal, and belongs to the technical field of information recommendation systems.
Background
The vending machine is a full-automatic machine which is transacted with customers through a currency detector, can assist the customers to purchase products such as snacks, beverages, wines, cigarettes, lottery tickets and the like, is a common commercial automatic device, is not limited by time and places, can save manpower and facilitate transactions, is a brand-new commercial retail form, is also called a 24-hour-business micro supermarket, and common vending machines comprise beverage vending machines, food vending machines, comprehensive vending machines, cosmetic vending machines and the like.
The Chinese patent publication No. CN 109191669A discloses an invisible commodity automatic selling system and a selling method, and the invisible commodity automatic selling system comprises a virtual commodity server terminal, a virtual commodity display module, a shopping selection module and an authentication management module of a vending machine terminal APP and/or a user terminal APP, and the invisible commodity automatic selling system realizes the function expansion of the existing automatic goods receiving machine by means of the Internet of things technology, a touch large screen and the cloud computing technology, realizes the safe automatic selling of valuables, large-sized articles and the like through the vending machine, can realize the shopping of a customer at any time and any place, breaks through the place limitation of the traditional vending machine, can only select the existing commodities by the user, cannot advance and classify the information of the user and send commodity recommendation information, cannot provide advertisement promotion and similar replaceable commodities for the customer, and leads to poor customer experience.
Because the current selling software APP of the unmanned retail terminal only concerns about commodities purchased by a customer, and the WeChat public number and the Paibao life number only concern about advertisement promotion of special commodities, the functions of recommending the users before and after purchasing through big data are not relevant, and high-grade and intelligent purchasing experience cannot be provided for the users.
Therefore, there is a need for an improved information recommendation system and method for an unmanned retail terminal to solve the above-mentioned problems.
Disclosure of Invention
The invention aims to provide an information recommendation system and method based on an unmanned retail terminal, which can provide more related, similar and matched products for a user before and after purchasing when the user purchases commodities, can pay through WeChat, Paibao and a credit card, and can receive and store the information of the user by a payment module in the payment process so as to push commodity information to the user.
In order to achieve the purpose, the invention adopts the main technical scheme that:
an information recommendation system based on an unmanned retail terminal comprises a retail cabinet body, wherein a server and a storage device are arranged inside the retail cabinet body, the server is connected with the storage device through a data connection line, a plurality of commodity placing bins are formed in the retail cabinet body, commodities to be sold are placed in the commodity placing bins, fetching covers are rotatably arranged on the commodity placing bins, two-dimensional codes are arranged on the fetching covers, and a main control module, a payment module and a display module are arranged on the retail cabinet body;
through the technical scheme, similar to a recommendation method for online website shopping, the server-specific recommendation algorithm is based on the big data accumulated by scanning the two-dimensional codes, the structure is simple, the use is convenient, only irregular goods are required to be put on the shelf, the cost of manual selling is saved, the selling cost is reduced, and the profit of selling is further improved;
the payment module is used for acquiring payment information and sending the payment information to the main control module after the acquisition is finished;
the main control module is used for receiving the payment information sent by the payment module and sending the payment information and information of commodities to be sold in the retail cabinet body to the server, the server transmits the information to the storage through the data connecting line, and the main control module generates commodity recommendation information according to the payment information;
the main control module is also used for sending the commodity recommendation information to the display module;
the display module is used for displaying the payment information and the commodity recommendation information;
the payment module comprises a WeChat payment module and a Paibao payment module, the payment module sends payment information to the server through the main control module, and the server sends WeChat public number promotion information or Paibao promotion information to the mobile payment terminal.
Preferably, the payment information includes WeChat payment information, Payment treasure payment information and credit card payment information.
Through the technical scheme, when a customer purchases commodities, more related, similar and matched products can be provided for the customer before and after purchasing, payment can be carried out through WeChat, Paibao and a credit card, meanwhile, in the payment process, the payment module can income and store the information of the customer so as to be convenient for pushing the commodity information to the customer, the storage is used for storing computer programs and user information, the server pushes public number promotion information or Paibao promotion information to the client side according to the storage, the WeChat payment information, Paibao payment information and credit card payment information are collected and then transmitted to the server and stored in the storage through the payment module, once the customer uses the commodity again, the server recommends similar commodities to the customer by calling the user payment information in the storage, big data processing is realized, and the efficiency is higher, more humanization and intellectualization.
Preferably, the storage is used for storing computer programs and user information, and the server pushes public number promotion information or payment promotion information to the client according to the storage.
The method for the information recommendation system based on the unmanned retail terminal machine is further provided, and comprises the following steps:
s1: scanning and paying the two-dimensional code through the mobile payment terminal;
s2: the payment module collects payment information and transmits the payment information to the server through the main control module, and the server sends the payment information to the storage;
s3: the main control module collects the user information and goods information of the mobile payment terminal, and groups the user data after being processed by the server;
s4: after new goods are put on shelf, the recommendation information is popularized to the mobile payment end through the server;
s5: when the user opens the mobile payment terminal again, the server recommends WeChat public number promotion information and Paibao promotion information to the mobile payment terminal;
s6: and when the customer uses the product again, the customer acquires the historical purchase record according to the user information and the payment information and pushes the commodity recommendation information.
Preferably, the two-dimensional code scanning payment mode of the mobile payment terminal is a WeChat payment mode, a Paibao payment mode and a credit card payment mode, and the payment module acquires the payment information and transmits the payment information to the server.
Through the technical scheme, when a user pays by WeChat, Payment treasure and credit card for the first time, the two-dimensional code of the commodity is scanned and paid by mobile payment terminals such as WeChat, Payment treasure and credit card, the payment module acquires the payment information and goods information of the user through the two-dimensional code, the acquired payment information and goods information are transmitted to the server through the main control template, the server calculates and processes the payment information and goods information and transmits the payment information and goods information to the storage and groups the payment information and goods information, meanwhile, the server pushes recommendation information similar to the commodity to the mobile payment terminal of the user, when the user uses the device again, the server calls the user payment information and user information in the storage and pushes the commodity recommendation information of related commodities to the mobile payment terminal of the user so as to change the user to select and purchase, the big data is processed to provide more choices for customers, and meanwhile, when the commodities are lack, the commodities can be provided to be replaced, so that the commodity rate is promoted, and the benefit can be maximized.
Preferably, the main control module collects user information of the mobile payment terminal, and groups user data after being processed by the server, wherein the user data is used for:
acquiring historical orders and purchasing quantities corresponding to various goods types of contrasting historical orders;
collecting sales gross profits corresponding to the historical orders and the goods types of the contrasted historical orders;
calculating a first recommendation right of each goods type according to the quantity and the gross profit;
and acquiring the goods types meeting the preset weight conditions, and using the goods types as the commodity recommendation information.
Preferably, the historical order further includes user identification information, and the user data is further used for:
collecting a user historical order corresponding to the user identification information;
and taking the user history order as the comparison history order.
Through the technical scheme, the server can calculate the quantity of each item purchased in the historical order of the user and the gross profit corresponding to each item type, select a commodity as the first weight, then push the commodity as the recommendation information of the commodity to the client, on the premise of meeting the requirement of customers on changing commodities, more gross profits are obtained, the selling profits are improved, by analyzing the target historical orders and contrasting the historical orders, so that the accurate inquiry is most consistent with the recommended commodity information of the corresponding vending machine to pertinently meet the commodity requirement of the user, the commodity recommendation of the vending machine with the same attribute by the operator is facilitated through the recommended commodity information, thereby effectively improving the commodity recommending efficiency and improving the user experience, and by sending the recommended commodity information to the server, the operation of replenishment or replacement is carried out on the cabinet body of the retail machine conveniently by an operator according to the recommended commodity.
Preferably, the method for wechat the public information in the step S5 includes the following steps:
s5.11: the server calculates for the WeChat payment user;
s5.12: the calculation results of step S5.11 are stored in the memory for grouping, and in each group, the nearest user to the user is determined;
s5.13: calculating the latest information attenuation coefficient according to all the WeChat public numbers concerned by the nearest user in the step S5.12 and the unit time of the corresponding WeChat public numbers;
s5.14: determining the set of recommended public numbers for the WeChat payment users;
s5.15: determining the final WeChat public number of the WeChat payment user according to the WeChat public numbers recommended by all groups for the WeChat payment user
Preferably, the method for paying the precious life number promotion information in step S5 includes the following steps:
s5.21: the server calculates for a pay payment user;
s5.22: the calculation results of step S5.21 are stored in the memory for grouping, and in each group, the nearest user to the user is determined;
s5.23: calculating the latest information attenuation coefficient according to all the pay treasure life numbers concerned by the nearest user in the step S5.22 and the unit time corresponding to the pay treasure life numbers;
s5.24: determining the recommended pay bank life number of the group of pay bank paying users;
s5.25: and determining the final payment treasure life number of the payment treasure payment user according to the payment treasure life number recommended by all groups for the payment treasure payment user.
Through above-mentioned technical scheme, communicate little communication public number and pay precious serial number to the nearest user propelling movement commodity recommendation information of user, can reach the purpose of popularization on the one hand, on the other hand is convenient for collect more user information to in the later stage arrange in order and the propelling movement to the user, promote system's intellectuality and hommization.
Preferably, in S5.22, the nearest user of the user is determined according to the following steps:
determining the personal tag of the payment treasure payment user according to the payment treasure life number concerned by the payment treasure payment user;
calculating the user matching degree of the payment user in each group in the storage according to the following formula;
in the above formula, FijRepresenting the matching degree of the Payment user and the jth user in the ith group, L representing the number of labels of the Payment user, max representing the element with the largest value in the set, sim representing a semantic similarity function, wlThe ith tag, m, representing the Payment userijsThe s label of the jth user in the ith group in the memory is represented, K represents the number of labels of the jth user in the ith group in the memory, the value of i is from 1 to N, N represents the number of groups in the memory, TiRepresenting the number of users in the ith group in the memory;
determining the nearest user according to the user matching degree;
Ri＝G(max{max{(Fij，Fiq)|q＜j}|j＝1，2，...，Ti})
in the above formula, RiRepresenting the number of the nearest user in the ith group in the memory, G representing the number extraction mapping function, FiqRepresenting the matching degree of the Payment user and the q-th user in the ith group;
the nearest user number and R in the ith group in the memoryiThe agreed is that the closest user in the group that the user pays for the payment instrument is inside the storage.
The invention has at least the following beneficial effects:
1. when the customer purchases the commodity, more related, similar and matched products can be provided for the customer before and after the purchase, the payment can be carried out through WeChat, Payment treasured and a credit card, and meanwhile, the payment module can income and store the information of the customer in the payment process so as to push the commodity information to the customer.
2. Through analyzing the target historical orders and contrasting the historical orders, the accurate inquiry is most consistent with the recommended commodity information of the corresponding vending machine, the commodity requirements of the user are met in a targeted mode, the commodity recommendation of the vending machine with the same attribute by an operator is facilitated through the recommended commodity information, the commodity recommendation efficiency is effectively improved, the user experience is improved, and the recommended commodity information is sent to the server, so that the operator can conveniently perform replenishment operation or substitute operation on the cabinet body of the retail machine according to the recommended commodities.
3. Commodity recommendation information is pushed to the nearest user of user to the public number of communicateing a little and the precious life number of payment, can reach the purpose of popularization on the one hand, and on the other hand is convenient for collect more user information to in the later stage arrange in order and the propelling movement to the user, promote system's intellectuality and hommization.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is an electrical schematic of the present invention;
FIG. 2 is a perspective view of a retail cabinet of the present invention;
FIG. 3 is a partial electrical schematic of the present invention;
FIG. 4 is a flow chart of the method of the present invention.
In the figure, 1-a retail machine cabinet body, 2-a commodity placing bin, 3-a commodity to be sold, 4-an article taking cover, 6-a two-dimensional code, 7-a display module, 8-a payment module, 9-a main control module, 10-a server, 11-a storage device and 12-a mobile payment end.
Detailed Description
Embodiments of the present application will be described in detail with reference to the drawings and examples, so that how to implement technical means to solve technical problems and achieve technical effects of the present application can be fully understood and implemented.
As shown in fig. 1 to 4, the information recommendation system based on the unmanned retail terminal provided in this embodiment includes a retail cabinet body 1, a server 10 and a storage 11 are disposed inside the retail cabinet body 1, the server 10 is connected to the storage 11 through a data connection line, a plurality of commodity placing bins 2 are disposed on the retail cabinet body 1, commodities 3 to be sold are placed inside the commodity placing bins 2, a fetching cover 4 is rotatably disposed on the commodity placing bins 2, a two-dimensional code 6 is disposed on the fetching cover 4, and a main control module 9, a payment module 8 and a display module 7 are disposed on the retail cabinet body 1;
similar to the recommendation method for online website shopping, the server 10 is used for scanning big data accumulated by the two-dimensional codes 6 and specifying a recommendation algorithm, the structure is simple, the use is convenient, only irregular commodities need to be put on shelves, the cost of manual selling is saved, the selling cost is reduced, and the profit of selling is further improved.
The payment module 8 is used for collecting payment information and sending the payment information to the main control module 9 after the collection is finished;
the main control module 9 is used for receiving the payment information sent by the payment module 8, sending the payment information and the information of the commodity 3 to be sold in the retail cabinet body 1 to the server 10, transmitting the information to the storage 11 by the server 10 through a data connection line, and generating commodity recommendation information by the main control module 9 according to the payment information;
the main control module 9 is also used for sending the commodity recommendation information to the display module 7;
the display module 7 is used for displaying payment information and commodity recommendation information, displaying information of commodities on shelves, commodity introduction and the like, performing multi-element display and improving the intelligence of the retail cabinet body 1;
the payment module 8 comprises a WeChat payment module and a Paibao payment module, the payment module 8 sends payment information to the server 10 through the main control module 9, and the server 10 sends WeChat public number promotion information or Paibao promotion information to the mobile payment terminal 12.
On unmanned APP of selling, WeChat public account and pay precious serial number, provide more relevant, similar, supporting products for the user before and after purchasing, supply the user to select or purchase, reach the level and the ability of promoting for customer service, send recommendation information to user's mobile terminal according to customer's purchase historical data and hobby degree, provide the commodity of recommending the most probable purchase for the user to promote user's the intelligent experience of shopping.
The payment information comprises WeChat payment information, Payment treasure payment information and credit card payment information, when a customer purchases commodities, more related, similar and matched products can be provided for the user before and after the purchase, payment can be carried out through WeChat, Payment treasure and credit card, meanwhile, in the payment process, the payment module 8 can receive and store the information of the customer so as to push the commodity information to the user, the storage 11 is used for storing a computer program and user information, the server 10 pushes public number promotion information or Payment treasure promotion information to the client according to the storage 11, after the payment module 8 collects the WeChat payment information, Payment treasure payment information and credit card payment information, the collected information is transmitted to the server 10 and stored in the storage 11, once the customer uses the payment information again, the server 10 recommends similar commodities to the user by calling the user payment information in the storage 11, big data processing, efficiency is higher, and is more humanized and intelligent.
The method of the information recommendation system based on the unmanned retail terminal comprises the following steps:
s1: scanning and paying the two-dimensional code 6 through the mobile paying terminal 12;
s2: the payment module 8 collects payment information and transmits the payment information to the server 10 through the main control module 9, and the server 10 sends the payment information to the storage 11;
s3: the main control module 9 collects the user information and goods information of the mobile payment terminal 12, and groups the user data after being processed by the server 10;
s4: after the new goods are put on the shelf, the recommendation information is promoted to the mobile payment terminal 12 through the server 10;
s5: when the user opens the mobile payment terminal 12 again, the server 10 recommends the WeChat public number promotion information and the Paibao promotion information to the mobile payment terminal 12;
s6: and when the customer uses the product again, the customer acquires the historical purchase record according to the user information and the payment information and pushes the commodity recommendation information.
In this embodiment, as shown in fig. 1, the two-dimensional code 6 is scanned and paid by the mobile payment terminal 12 in a WeChat payment mode, a Paibao payment mode, and a credit card payment mode, and the payment module 8 obtains payment information and transmits the payment information to the server 10.
When a user pays by WeChat, Payment treasures and a credit card for the first time, scanning and paying the two-dimensional code 6 of the commodity by a mobile payment terminal 12 such as WeChat, Payment treasures and a credit card, then obtaining payment information and goods information of the user by a payment module 8 through the two-dimensional code 6, then transmitting the collected payment information and goods information to a server 10 through a main control template, calculating and processing the payment information and goods information by the server 10, transmitting the payment information and goods information to a storage 11 and grouping the payment information and goods information, simultaneously pushing recommendation information similar to the commodity to the mobile payment terminal 12 of the user by the server 10, calling the payment information and the user information of the user in the storage 11 by the server 10 when the user uses the mobile payment terminal 12 of the user again, pushing the recommendation information of the commodity of the related commodity to the mobile payment terminal 12 of the user so as to select and purchase the user instead, the big data is processed to provide more choices for customers, and meanwhile, when the commodities are lack, the commodities can be provided to be replaced, so that the commodity rate is promoted, and the benefit can be maximized.
The main control module 9 collects the user information of the mobile payment terminal 12, and groups the user data after being processed by the server 10, wherein the user data is used for:
acquiring historical orders and purchasing quantities corresponding to various goods types of contrasting historical orders;
collecting sales gross profits corresponding to the historical orders and various goods types of the contrasted historical orders;
calculating a first recommendation right of each goods type according to the quantity and the gross profit;
and acquiring the goods types meeting the preset weight conditions and using the goods types as goods recommendation information.
The historical order also contains user identification information, and the user data can be further used for:
collecting a user historical order corresponding to the user identification information;
and taking the user history order as a comparison history order.
The server 10 may calculate the number of each item purchased in the user's historical order and the gross profit corresponding to each item type, select a commodity as the first weight, and then push it to the client as the recommendation information of the commodity, on the premise of meeting the requirement of customers on changing commodities, more gross profits are obtained, the selling profits are improved, by analyzing the target historical orders and contrasting the historical orders, so that the accurate inquiry is most consistent with the recommended commodity information of the corresponding vending machine to pertinently meet the commodity requirement of the user, the commodity recommendation of the vending machine with the same attribute by the operator is facilitated through the recommended commodity information, thereby effectively improving the efficiency of recommending commodities and improving the user experience, by transmitting the recommended commodity information to the server 10, the operation of replenishment or replacement is carried out on the cabinet body of the retail machine conveniently by an operator according to the recommended commodity.
The method for wechat the public information promotion information in the step S5 includes the following steps:
s5.11: the server 10 performs calculations for the WeChat Payment user;
s5.12: the calculation results of step S5.11 are stored in the memory 11 for grouping, and in each group, the nearest user to the user is determined;
s5.13: calculating the latest information attenuation coefficient according to all the WeChat public numbers concerned by the nearest user in the step S5.12 and the unit time of the corresponding WeChat public numbers;
s5.14: determining the set of recommended public numbers for the WeChat payment users;
s5.15: and determining the final WeChat public number of the WeChat payment user according to the WeChat public numbers recommended by all groups for the WeChat payment users.
The method for paying the precious life number promotion information in the step S5 comprises the following steps:
s5.21: the server 10 calculates for the pay-for-treasure payment user;
s5.22: the calculation results of step S5.21 are stored in the memory 11 and grouped, and within each group, the nearest user to the user is determined;
s5.23: calculating the latest information attenuation coefficient according to all the pay treasure life numbers concerned by the nearest user in the step S5.22 and the unit time corresponding to the pay treasure life numbers;
s5.24: determining the recommended pay bank life number of the group of pay bank paying users;
s5.25: and determining the final payment treasure life number of the payment treasure payment user according to the payment treasure life numbers recommended by all groups for the payment treasure payment users.
Commodity recommendation information is pushed to the nearest user of user to the public number of communicateing a little and the precious life number of payment, can reach the purpose of popularization on the one hand, and on the other hand is convenient for collect more user information to in the later stage arrange in order and the propelling movement to the user, promote system's intellectuality and hommization.
Similar to the recommendation method for online website shopping, the server 10 is used for scanning big data accumulated by the two-dimensional codes 6 and specifying a recommendation algorithm, the structure is simple, the use is convenient, only irregular commodities need to be put on shelves, the cost of manual selling is saved, the selling cost is reduced, and the profit of selling is further improved.
When the customer purchases the commodity, more related, similar and matched products can be provided for the customer before and after the purchase, the payment can be carried out through WeChat, Payment treasured and a credit card, and meanwhile, in the payment process, the payment module 8 can income and store the information of the customer so as to push the commodity information to the customer.
On unmanned APP of selling, WeChat public account and pay precious serial number, provide more relevant, similar, supporting products for the user before and after purchasing, supply the user to select or purchase, reach the level and the ability of promoting for customer service, send recommendation information to user's mobile terminal according to customer's purchase historical data and hobby degree, provide the commodity of recommending the most probable purchase for the user to promote user's the intelligent experience of shopping.
In S5.22, the nearest neighbor of the user is determined according to the following steps:
determining the personal tag of the payment treasure payment user according to the payment treasure life number concerned by the payment treasure payment user;
calculating the user matching degree of the payment user in each group in the storage according to the following formula;
in the above formula, FijRepresenting the matching degree of the Payment user and the jth user in the ith group, L representing the number of labels of the Payment user, max representing the element with the largest value in the set, sim representing a semantic similarity function, wlThe ith tag, m, representing the Payment userijsThe s label of the jth user in the ith group in the memory is represented, K represents the number of labels of the jth user in the ith group in the memory, the value of i is from 1 to N, N represents the number of groups in the memory, TiRepresenting the number of users in the ith group in the memory;
determining the nearest user according to the user matching degree;
Ri＝G(max{max{(Fij，Fiq)|q＜j}|j＝1，2，...，Ti})
in the above formula, RiRepresenting the number of the nearest user in the ith group in the memory, G representing the number extraction mapping function, FiqRepresenting the matching degree of the Payment user and the q-th user in the ith group;
the nearest user number and R in the ith group in the memoryiThe agreed is that the closest user in the group that the user pays for the payment instrument is inside the storage.
In step S5.22, when it is determined that the user who pays the treasures is the nearest to the user in each group, the user matching degree of the user who pays the treasures in each group inside the storage is determined according to the semantic similarity value between the tag of the user who pays the treasures and the tag of the user in each group inside the storage, so that the user who pays the treasures in each group inside the storage can be accurately identified for the tags which have the same semantic meaning but different expressions when the user matching degree of the user who pays the treasures in each group inside the storage is calculated, and the calculation accuracy of the matching degree is further improved. By formula R in determining adjacent usersi＝G(max{max{(Fij，Fiq)|q＜j}|j＝1，2，...，TiAnd) the numbers of the nearest users in the groups can be directly obtained, so that the nearest users can be quickly determined, the efficiency of determining the nearest users in each group is improved, and the time consumed by information recommendation is reduced.
As used in the specification and in the claims, certain terms are used to refer to particular components. As one skilled in the art will appreciate, manufacturers may refer to a component by different names. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. "substantially" means within an acceptable error range, and a person skilled in the art can solve the technical problem within a certain error range to achieve the technical effect basically.
It is noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of additional like elements in the article or system in which the element is included.
The foregoing description shows and describes several preferred embodiments of the invention, but as aforementioned, it is to be understood that the invention is not limited to the forms disclosed herein, but is not to be construed as excluding other embodiments and is capable of use in various other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. An information recommendation system based on an unmanned retail terminal comprises a retail cabinet body (1) and is characterized in that a server (10) and a storage device (11) are arranged inside the retail cabinet body (1), the server (10) is connected with the storage device (11) through a data connection line, a plurality of commodity placing bins (2) are formed in the retail cabinet body (1), commodities (3) to be sold are placed inside the commodity placing bins (2), an object taking cover (4) is rotatably arranged on the commodity placing bins (2), two-dimensional codes (6) are arranged on the object taking cover (4), and a main control module (9), a payment module (8) and a display module (7) are arranged on the retail cabinet body (1);
the payment module (8) is used for collecting payment information and sending the payment information to the main control module (9) after collection is finished;
the main control module (9) is configured to receive the payment information sent by the payment module (8), send the payment information and information of the to-be-sold goods (3) inside the retail machine cabinet body (1) to the server (10), the server (10) transmits the information to the storage (11) through the data connection line, and the main control module (9) generates goods recommendation information according to the payment information;
the main control module (9) is also used for sending the commodity recommendation information to the display module (7);
the display module (7) is used for displaying the payment information and the commodity recommendation information;
the payment module (8) comprises a WeChat payment module and a Paibao payment module, the payment module (8) is used for sending payment information to the server (10) through the main control module (9), and the server (10) is used for sending WeChat public number promotion information and Paibao promotion information to the mobile payment terminal (12);
the method for the server (10) to send the payment treasure popularization information to the mobile payment terminal (12) comprises the following steps:
s5.21: the server (10) calculates for a pay-for-use user;
s5.22: the calculation results of step S5.21 are stored in the memory (11) and grouped, and in each group, the nearest user of the user is determined;
s5.23: calculating the latest information attenuation coefficient according to all the pay treasure life numbers concerned by the nearest user in the step S5.22 and the unit time corresponding to the pay treasure life numbers;
s5.24: determining the recommended pay bank life number of the group of pay bank paying users;
s5.25: determining the final pay treasure life number of the pay treasure payment user according to the pay treasure life number recommended by all groups for the pay treasure payment user;
in S5.22, the nearest neighbor of the user is determined according to the following steps:
determining the personal tag of the payment treasure payment user according to the payment treasure life number concerned by the payment treasure payment user;
calculating the user matching degree of the payment user in each group in the storage according to the following formula;
in the above-mentioned formula,
indicating the Payment user and the second
In the group
The degree of matching of the first-name users,
a number of tags representing a user to which the payment instrument pays,
indicating the element with the largest value taken in the set,
a function of semantic similarity is represented by a function of semantic similarity,
second to represent the Payment user
The number of the labels is one,
indicating internal to memory
In the group
First of a user
The number of the labels is one,
indicating internal to memory
In the group
The number of tags for the first user,
is taken from 1 to N, N representing the number of packets inside the memory,
indicating internal to memory
The number of users in the group;
determining the nearest user according to the user matching degree;
in the above-mentioned formula,
indicating internal to memory
The number of the nearest user in the group,
a number extraction mapping function is represented that is,
indicating the Payment user and the second
In the group
Matching degree of the first user;
in the memory interior
The nearest user number in the group and
the agreed is that the closest user in the group that the user pays for the payment instrument is inside the storage.
2. The unmanned retail terminal-based information recommendation system according to claim 1, wherein: the payment information comprises WeChat payment information, Paibao payment information and credit card payment information.
3. The unmanned retail terminal-based information recommendation system according to claim 1, wherein: the storage device (11) is used for storing computer programs and user information, and the server (10) pushes WeChat public number promotion information and Paibao promotion information to the client according to the storage device (11).
4. An information recommendation method based on an unmanned retail terminal is characterized by comprising the following steps:
s1: scanning and paying the two-dimensional code (6) through a mobile paying terminal (12);
s2: the payment module (8) collects payment information and transmits the payment information to the server (10) through the main control module (9), and the server (10) sends the payment information to the storage device (11);
s3: the main control module (9) collects the user information and goods information of the mobile payment terminal (12), and groups the user data after being processed by the server (10);
s4: after new goods are put on the shelf, recommending information is popularized to the mobile payment terminal (12) through the server (10);
s5: when the user opens the mobile payment terminal (12) again, the server (10) recommends the WeChat public number promotion information and the Paibao promotion information to the mobile payment terminal (12);
s6: when the customer uses the system again, the customer acquires a historical purchase record according to the user information and the payment information and pushes commodity recommendation information;
the method for recommending the treasured payment promotion information in the step S5 includes the following steps:
s5.21: the server (10) calculates for a pay-for-use user;
s5.22: the calculation results of step S5.21 are stored in the memory (11) and grouped, and in each group, the nearest user of the user is determined;
s5.23: calculating the latest information attenuation coefficient according to all the pay treasure life numbers concerned by the nearest user in the step S5.22 and the unit time corresponding to the pay treasure life numbers;
s5.24: determining the recommended pay bank life number of the group of pay bank paying users;
s5.25: determining the final pay treasure life number of the pay treasure payment user according to the pay treasure life number recommended by all groups for the pay treasure payment user;
in S5.22, the nearest neighbor of the user is determined according to the following steps:
determining the personal tag of the payment treasure payment user according to the payment treasure life number concerned by the payment treasure payment user;
calculating the user matching degree of the payment user in each group in the storage according to the following formula;
in the above-mentioned formula,
indicating the Payment user and the second
In the group
The degree of matching of the first-name users,
a number of tags representing a user to which the payment instrument pays,
indicating the element with the largest value taken in the set,
a function of semantic similarity is represented by a function of semantic similarity,
second to represent the Payment user
The number of the labels is one,
indicating internal to memory
In the group
First of a user
The number of the labels is one,
indicating internal to memory
In the group
The number of tags for the first user,
is taken from 1 to N, N representing the number of packets inside the memory,
indicating internal to memory
The number of users in the group;
determining the nearest user according to the user matching degree;
in the above-mentioned formula,
indicating internal to memory
The number of the nearest user in the group,
a number extraction mapping function is represented that is,
indicating the Payment user and the second
In the group
Matching degree of the first user;
in the memory interior
The nearest user number in the group and
the agreed is that the closest user in the group that the user pays for the payment instrument is inside the storage.
5. The information recommendation method based on unmanned retail terminal set according to claim 4, characterized in that: the mobile payment terminal (12) scans the two-dimensional code (6) to pay in a WeChat payment mode, a Paibao payment mode and a credit card payment mode, and the payment module (8) acquires the payment information and transmits the payment information to the server (10).
6. The information recommendation method based on unmanned retail terminal set according to claim 4, characterized in that: the main control module (9) collects the user information of the mobile payment terminal (12), and groups user data after being processed by the server (10), wherein the user data is used for collecting historical orders and contrasting the purchase quantity corresponding to each goods type of the historical orders;
the user data is also used for collecting sales gross profits corresponding to the historical orders and various goods types of the contrasted historical orders;
calculating a first recommendation right of each goods type according to the purchase quantity and the sales margin;
and acquiring the goods types meeting the preset weight conditions, and using the goods types as the commodity recommendation information.
7. The information recommendation method based on unmanned retail terminal set according to claim 6, characterized in that: the historical order further comprises user identification information, and the user data is also used for collecting the historical user order corresponding to the user identification information;
and taking the user history order as the comparison history order.
8. The information recommendation method based on unmanned retail terminal set according to claim 4, characterized in that: the method for wechat the public information promotion information in the step S5 includes the following steps:
s5.11: the server (10) performs calculations for a WeChat payment user;
s5.12: the calculation results of step S5.11 are stored in the memory (11) and grouped, and in each group, the nearest user of the user is determined;
s5.13: calculating the latest information attenuation coefficient according to all the WeChat public numbers concerned by the nearest user in the step S5.12 and the unit time of the corresponding WeChat public numbers;
s5.14: determining the set of recommended public numbers for the WeChat payment users;
s5.15: and determining the final WeChat public number of the WeChat payment user according to the WeChat public numbers recommended by all groups for the WeChat payment users.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103092911A (en) * | 2012-11-20 | 2013-05-08 | 北京航空航天大学 | K-neighbor-based collaborative filtering recommendation system for combining social label similarity |
| CN105160542A (en) * | 2015-07-27 | 2015-12-16 | 张志军 | Cloud control intelligent food sale system and realization method of the system |
| CN109658207A (en) * | 2019-01-15 | 2019-04-19 | 深圳友朋智能商业科技有限公司 | Method of Commodity Recommendation, system and the device of automatic vending machine |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103092911A (en) * | 2012-11-20 | 2013-05-08 | 北京航空航天大学 | K-neighbor-based collaborative filtering recommendation system for combining social label similarity |
| CN105160542A (en) * | 2015-07-27 | 2015-12-16 | 张志军 | Cloud control intelligent food sale system and realization method of the system |
| CN109658207A (en) * | 2019-01-15 | 2019-04-19 | 深圳友朋智能商业科技有限公司 | Method of Commodity Recommendation, system and the device of automatic vending machine |
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