Online shopping mall point exchange management method and system based on point mechanism

Abstract

The embodiment of the invention relates to the technical field of marketing management, and particularly discloses an online shopping mall point exchange management method and system based on a point mechanism. According to the embodiment of the invention, online browsing data and online point data are obtained; matching point vouchers corresponding to the plurality of online interested commodities; when the user carries out offline shopping, commodity settlement matching is carried out; performing multi-source verification on the target user; and during offline shopping settlement, a plurality of target vouchers are automatically deducted. The method can determine a plurality of online interested commodities of an online shopping mall of a target user, match a plurality of point vouchers, perform commodity settlement matching, select a plurality of target interested commodities and a plurality of target vouchers during offline shopping, and perform automatic deduction under the condition that multi-source verification succeeds. According to the invention, online and offline intercommunication of mall point exchange based on a point mechanism is realized, manual operation of a user is not needed, the purpose of promoting consumption can be realized, and the shopping experience of the user can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of marketing management, and in particular to an online shopping mall points redemption management method and system based on a points mechanism. Background Art

[0002] Shopping marketing management technology is the specific application of marketing management technology in shopping scenarios or retail industries. Through a series of strategies, methods and tools, it effectively plans, executes and controls marketing activities in a shopping environment with the focus on meeting customer needs to achieve marketing goals.

[0003] With the development of digital technology, shopping marketing management technology is also showing a digital trend.

[0004] In the prior art, mall point redemption based on the point mechanism is usually not interoperable between online and offline, resulting in limited usage scenarios of point redemption and failure to achieve the purpose of promoting consumption. In addition, mall point redemption based on the point mechanism is usually cumbersome, requiring users to manually redeem and deduct vouchers, which often cannot maximize the promotion effect and affects the user's shopping experience. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide an online shopping mall points redemption management method and system based on a points mechanism, aiming to solve the problems raised in the background technology.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: An online shopping mall points exchange management method based on a points mechanism, the method specifically comprises the following steps: Obtain the service management authority of the target user, track and record the target user's shopping browsing in the online mall, and obtain online browsing data and online points data; Performing interest analysis on the online browsing data to determine a plurality of online products of interest, and matching the plurality of point vouchers corresponding to the online products of interest according to the online point data; When the user is shopping offline, offline settlement information is obtained, and commodity settlement matching is performed based on the plurality of online commodities of interest to determine whether the matching is successful; When the match is successful, multiple target interest products and multiple target vouchers are selected, and multi-source verification is performed on the target user to determine whether the verification is successful; When the verification is successful, multiple target vouchers are exchanged, and when the offline shopping is settled, multiple target vouchers are automatically deducted, and the online points data is updated.

[0007] An online shopping mall points redemption management system based on a points mechanism, the system includes an online tracking and recording unit, an interest analysis processing unit, a commodity settlement matching unit, a multi-source verification and judgment unit, and a voucher deduction processing unit, wherein: The online tracking and recording unit is used to obtain the service management authority of the target user, track and record the target user's shopping browsing in the online mall, and obtain online browsing data and online points data; An interest analysis processing unit, configured to perform interest analysis on the online browsing data, determine a plurality of online interest commodities, and match a plurality of point vouchers corresponding to the online interest commodities according to the online point data; A commodity settlement matching unit, used to obtain offline settlement information when the user is shopping offline, and to match the commodity settlement based on the plurality of online commodities of interest, and to determine whether the matching is successful; A multi-source verification judgment unit is used to select multiple target interest commodities and multiple target vouchers when the match is successful, and perform multi-source verification on the target user to determine whether the verification is successful; The voucher deduction processing unit is used to redeem multiple target vouchers when the verification is successful, automatically deduct multiple target vouchers when settling offline shopping, and update the online points data.

[0008] Compared with the prior art, the present invention has the following beneficial effects: The embodiment of the present invention obtains online browsing data and online points data; matches points vouchers corresponding to multiple online interest commodities; performs commodity settlement matching when the user performs offline shopping; performs multi-source verification on the target user; and automatically deducts multiple target vouchers during offline shopping settlement. It is possible to determine multiple online interest commodities of the target user in the online mall, match multiple points vouchers, and perform commodity settlement matching when shopping offline, select multiple target interest commodities and multiple target vouchers, and automatically deduct when the multi-source verification is successful, thereby realizing the intercommunication between online and offline mall points exchange based on the points mechanism, without the need for manual operation by the user, achieving the purpose of promoting consumption, and improving the user's shopping experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0010] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0011] Figure 2A flow chart of tracking and recording shopping browsing in the method provided by an embodiment of the present invention is shown.

[0012] Figure 3 A flowchart of interest analysis and matching processing in the method provided by an embodiment of the present invention is shown.

[0013] Figure 4 A flow chart of commodity settlement matching in the method provided in an embodiment of the present invention is shown.

[0014] Figure 5 A flow chart of performing offline multi-source verification in the method provided by an embodiment of the present invention is shown.

[0015] Figure 6 A flow chart of automatic deduction of target vouchers in the method provided by an embodiment of the present invention is shown.

[0016] Figure 7 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0017] Figure 8 The structure block diagram of the online tracking and recording unit in the system provided by the embodiment of the present invention is shown.

[0018] Fig. 9 A structural block diagram of an interest analysis processing unit in a system provided by an embodiment of the present invention is shown.

[0019] Fig.10 The structure block diagram of the multi-source verification judgment unit in the system provided by the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] It is understandable that in the prior art, mall point redemption based on the point mechanism is usually not interoperable between online and offline, resulting in limited usage scenarios of point redemption and failure to achieve the purpose of promoting consumption. In addition, mall point redemption based on the point mechanism is usually cumbersome, requiring users to manually select, redeem and deduct vouchers, which often cannot maximize the promotional effect and affects the user's shopping experience.

[0022] To solve the above problems, the embodiments of the present invention obtain the service management authority of the target user, track and record the shopping browsing of the target user in the online mall, and obtain online browsing data and online points data; perform interest analysis on the online browsing data, determine multiple online interest products, and match the points vouchers corresponding to the multiple online interest products according to the online points data; when the user conducts offline shopping, obtain offline settlement information, and perform product settlement matching based on the multiple online interest products to determine whether the matching is successful; when the matching is successful, select multiple target interest products and multiple target vouchers, and perform multi-source verification on the target user to determine whether the verification is successful; when the verification is successful, redeem multiple target vouchers, and automatically deduct multiple target vouchers during offline shopping settlement, and update the online points data. It can determine multiple online products of interest to target users in the online mall, match multiple points vouchers, and perform product settlement matching when shopping offline. It can select multiple target products of interest and multiple target vouchers, and automatically deduct them when multi-source verification is successful, thereby realizing the interoperability of mall points redemption based on the points mechanism between online and offline without the need for manual operation by users, thus achieving the purpose of promoting consumption and enhancing the user's shopping experience.

[0023] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0024] Specifically, the online shopping mall points redemption management method based on the points mechanism includes the following steps: Step S101, obtaining the service management authority of the target user, tracking and recording the target user's shopping browsing in the online mall, and obtaining online browsing data and online points data.

[0025] In an embodiment of the present invention, a permission application is generated and sent to a mobile terminal of a target user. The target user can view the permission application on the mobile terminal, agree or reject the permission application, and provide feedback. By receiving the application feedback from the mobile terminal of the target user, the application feedback is content identified. When the target user accepts the permission application, the service management authority of the target user is obtained. Based on the service management authority, the shopping browsing of the target user in the online mall is tracked and recorded, and online browsing data and online points data are obtained.

[0026] Specifically, Figure 2 A flow chart of tracking and recording shopping browsing in the method provided by an embodiment of the present invention is shown.

[0027] Among them, in the preferred implementation mode provided by the present invention, the obtaining of the service management authority of the target user, tracking and recording the shopping browsing of the target user in the online mall, and obtaining the online browsing data and online points data specifically include the following steps: Step S1011, generating and sending a permission request to a target user; Step S1012, receiving application feedback from the target user regarding the permission application; Step S1013, according to the application feedback, when the target user accepts the permission application, obtaining the service management permission of the target user; Step S1014: Based on the service management authority, the target user's shopping browsing in the online mall is tracked and recorded to obtain online browsing data and online points data.

[0028] In the preferred embodiment provided by the present invention, tracking and recording the target user's shopping browsing in the online mall, and obtaining the online browsing data and online points data specifically include the following steps: When users browse the online store, the product ID, timestamp and browsing duration are recorded; Calculate the total browsing time of the target user by adding up the browsing time in all browsing records of the target user; Identify the target user’s peak browsing time by calculating the timestamps that appear most frequently in the user’s browsing data; If the target user has a corresponding browsing record, the user's total browsing time and peak browsing time are used as feature inputs, and the user's browsing pattern is classified using a clustering algorithm to obtain the user behavior clustering result; Perform Fourier transform on the browsing time of each browsing record, and compare the frequency components in the Fourier transform result with the browsing peak time as a reference to obtain the periodicity analysis result; The corresponding points are calculated and distributed to users based on the total browsing time, peak browsing time, user behavior clustering results and periodic analysis results.

[0029] Furthermore, the online shopping mall points exchange management method based on the points mechanism also includes the following steps: Step S102, performing interest analysis on the online browsing data, determining a plurality of online interest commodities, and matching the plurality of point vouchers corresponding to the online interest commodities according to the online point data.

[0030] In an embodiment of the present invention, by performing product analysis on online browsing data, multiple online browsing products browsed by target users in an online mall are determined, and then based on the multiple online browsing products, a time statistical analysis is performed on the online browsing data to obtain the browsing time of the multiple online browsing products, and a number statistical analysis is performed on the online browsing data to obtain the number of views of the multiple online browsing products. Using the multiple browsing times and the multiple browsing times as evaluation indicators, an interest comparison is performed on the multiple online browsing products, and multiple online interest products are selected. Based on a preset point mechanism, the online point data is analyzed to match point vouchers corresponding to the multiple online interest products.

[0031] It is understandable that the preset points mechanism can be membership status, shopping requirements, usage time requirements, etc.

[0032] Specifically, Figure 3 A flowchart of interest analysis and matching processing in the method provided by an embodiment of the present invention is shown.

[0033] Among them, in the preferred implementation mode provided by the present invention, the performing interest analysis on the online browsing data, determining a plurality of online interest commodities, and matching the point vouchers corresponding to the plurality of online interest commodities according to the online point data specifically comprises the following steps: Step S1021, performing commodity analysis on the online browsing data to determine a plurality of online browsing commodities; Step S1022, performing a duration statistical analysis on the online browsing data to obtain the browsing duration of a plurality of online browsed products; Step S1023, performing a frequency statistical analysis on the online browsing data to obtain the number of times of browsing of the plurality of online browsed products; Step S1024, comparing the interests of the plurality of online browsed products according to the plurality of browsing durations and the plurality of browsing times, and selecting a plurality of online interest products; Step S1025: Based on a preset points mechanism, the online points data is analyzed to match points vouchers corresponding to a plurality of online products of interest.

[0034] In a preferred embodiment of the present invention, comparing the interests of the plurality of online browsed products according to the plurality of browsing durations and the plurality of browsing times, and selecting the plurality of online interest products specifically comprises the following steps: Obtain multiple browsing durations and multiple browsing times, and determine the median values ​​corresponding to the browsing durations and browsing times; If the browsing time and browsing times are greater than the corresponding median value, a value of 1 is assigned; if it is less than the corresponding median value, the browsing time and browsing times are standardized to between [0,1] to obtain the fuzzy logic membership value of the browsing time and browsing times; According to the deviation of the user's browsing time and browsing times from the median, a smoothing function is used to calculate the adaptive weight; Perform weighted aggregation on the fuzzy logic membership values ​​of the browsing time and browsing times and the corresponding adaptive weights to obtain an aggregation result, and divide the aggregation result by the sum of the adaptive weights to obtain a comprehensive interest score; The comprehensive interest score is normalized using softmax to obtain the probability distribution, and online interest products are selected based on the probability distribution.

[0035] In an embodiment of the present invention, the traditional hard threshold may be too strict. The present invention can better handle the uncertainty and ambiguity in user behavior through the method of fuzzy logic. Fuzzy logic allows that part of the user's interests are still considered when the user's behavior is close to the threshold, which can more truly reflect the user's potential interests. In addition, the present invention also introduces adaptive weights, which use adaptive weights to allow the model to dynamically adjust the importance according to user behavior. This means that for those users who significantly deviate from the median in a certain dimension (such as extremely long browsing time or high frequency of visits), the system can pay more attention to it, thereby better capturing the user's true interests. Finally, the information analysis of the two dimensions is combined to make the evaluation of user interests more comprehensive and accurate.

[0036] Furthermore, the online shopping mall points exchange management method based on the points mechanism also includes the following steps: Step S103, when the user performs offline shopping, offline settlement information is obtained, and commodity settlement matching is performed based on the plurality of online commodities of interest to determine whether the matching is successful.

[0037] In an embodiment of the present invention, when a user conducts offline shopping, offline settlement information is obtained, and multiple offline settlement commodities are determined by identifying commodities in the offline settlement information. Then, based on multiple online commodities of interest, multiple offline settlement commodities are matched to determine whether the matching is successful.

[0038] Specifically, Figure 4 A flow chart of commodity settlement matching in the method provided in an embodiment of the present invention is shown.

[0039] Among them, in the preferred implementation mode provided by the present invention, when the user performs offline shopping, offline settlement information is obtained, and commodity settlement matching is performed based on the plurality of online commodities of interest, and determining whether the matching is successful specifically includes the following steps: Step S1031, when the user performs offline shopping, obtaining offline settlement information; Step S1032, identifying commodities for the offline settlement information to determine a plurality of offline settlement commodities; Step S1033: Match the multiple offline settlement products based on the multiple online interest products to determine whether the matching is successful.

[0040] In a preferred embodiment of the present invention, based on the multiple online interest products, the multiple offline settlement products are matched, and judging whether the matching is successful specifically includes the following steps: The features of the online interest products and offline settlement products are converted into feature vectors in numerical form by word embedding, so as to obtain multiple feature vectors for each online interest product and offline settlement product; wherein the features of the online interest products and offline settlement products include name, category, and price; Assign weights to multiple feature vectors respectively, calculate the cosine similarity of each feature vector between the online interest products and the offline settlement products, and multiply the cosine similarity of each feature vector by the corresponding weight to obtain the contribution of the corresponding feature; The contribution of multiple features is accumulated to obtain the total similarity score of the product pair; A matching threshold is set, and product pairs with a total similarity score higher than the matching threshold are defined as successfully matched product pairs.

[0041] In an embodiment of the present invention, by considering multiple features, each feature provides a different information dimension, thereby increasing the accuracy of the match. In addition, the importance of different features can be adjusted by weights. This flexibility allows the system to adjust the influence of each feature in the similarity calculation according to actual needs to adapt to different business scenarios. And as the market or product characteristics change, the feature weights and similarity thresholds can be dynamically adjusted to ensure that the system can always provide the best matching results. Finally, fuzzy logic is used to determine whether the similarity is high enough for a successful match, which allows the system to be more flexible in dealing with uncertainty and ambiguity. It avoids misjudgments caused by hard thresholds and improves the rationality of matching.

[0042] Furthermore, the online shopping mall points exchange management method based on the points mechanism also includes the following steps: Step S104, when the matching is successful, multiple target interest commodities and multiple target vouchers are selected, and multi-source verification is performed on the target user to determine whether the verification is successful.

[0043] In an embodiment of the present invention, when a match is possible, a plurality of successfully matched target interest commodities are selected from a plurality of online interest commodities, and then a plurality of target vouchers corresponding to the target interest commodities are selected from a plurality of point vouchers. Thereafter, identity authentication is performed on the target user and the identity authentication result is recorded. Then, location verification is performed on the target user and the location verification result is recorded. In addition, relevant online and offline verifications are performed on the target user and the relevant verification results are recorded. A comprehensive analysis of the identity authentication result, location verification result and relevant verification results is performed to determine whether the verification is successful.

[0044] It can be understood that identity verification can be fingerprint verification, facial recognition verification, etc., to determine whether the target user is the user himself; location verification can be to obtain the positioning data of the target user's mobile terminal to determine whether the offline payment is in the area where the voucher can be redeemed; related online and offline verifications can be to identify the WiFi connection signal, Bluetooth connection signal, etc. of the target user's mobile terminal to determine the offline mall where the target user is located, and determine whether the offline mall is an authorized mall of the online mall.

[0045] Specifically, Figure 5 A flow chart of performing offline multi-source verification in the method provided by an embodiment of the present invention is shown.

[0046] Among them, in the preferred implementation mode provided by the present invention, when the matching is successful, multiple target interest commodities and multiple target vouchers are selected, and multi-source verification is performed on the target user, and determining whether the verification is successful specifically includes the following steps: Step S1041, when the matching is successful, selecting a plurality of target interest products from the plurality of online interest products; Step S1042, selecting target vouchers corresponding to multiple target interest commodities from the multiple point vouchers; Step S1043, authenticate the target user and record the authentication result; Step S1044, performing location verification on the target user and recording the location verification result; Step S1045, performing relevant online and offline verification on the target user, and recording relevant verification results; Step S1046, comprehensively analyzing the identity verification result, the location verification result and the related verification result to determine whether the verification is successful.

[0047] In a preferred embodiment of the present invention, judging whether the verification is successful by combining the identity verification result, the location verification result and the related verification result specifically includes the following steps: Map the identity verification result, location verification result, and related verification result to a score between 0 and 1 to obtain an identity verification score, a location verification score, and a related verification score; Based on the user's historical behavior data, the conditional probability of identity verification is calculated. When the identity verification result is known, the conditional probability of location verification is calculated. Based on the result of location verification, the conditional probability of related verification is calculated. Multiply the conditional probability of identity verification, the conditional probability of location verification, and the conditional probability of correlation verification to get the joint probability; According to the periodic fluctuations of user browsing over time in history, the identity verification score, location verification score and related verification score are given time dynamic weights, and then weighted sum calculation is performed to obtain a preliminary comprehensive score; Given a verification threshold, the preliminary comprehensive score is multiplied by the joint probability to obtain the final comprehensive score, and then the final comprehensive score is compared with the verification threshold to determine whether the verification is successful.

[0048] In the embodiment of the present invention, the conditional dependency between various verification factors is fully considered through joint probability, so that the verification process is not just a simple score addition, but a more comprehensive risk assessment, thereby ensuring the comprehensiveness of the assessment; and through time dynamic weight adjustment, the importance of verification can be automatically adjusted according to the security requirements of different time periods. This dynamic adjustment can adapt to different security strategies during peak and non-peak periods. The present invention can reduce the possibility of misjudgment and erroneous verification by combining multiple verification dimensions and fine adjustment of their weights.

[0049] Furthermore, the online shopping mall points exchange management method based on the points mechanism also includes the following steps: Step S105, when the verification is successful, multiple target vouchers are exchanged, and multiple target vouchers are automatically deducted during offline shopping settlement, and the online points data is updated.

[0050] In an embodiment of the present invention, if the verification is successful, the target user's points are exchanged for multiple target vouchers in the online mall, and then the multiple target vouchers are automatically deducted during offline shopping settlement. After the settlement is completed, the points deduction data is obtained, and then the online points data is synchronously updated based on the points deduction data.

[0051] Specifically, Figure 6 A flow chart of automatic deduction of target vouchers in the method provided by an embodiment of the present invention is shown.

[0052] Among them, in the preferred embodiment provided by the present invention, when the verification is successful, exchanging multiple target vouchers, automatically deducting multiple target vouchers during offline shopping settlement, and updating the online points data specifically include the following steps: Step S1051, when the verification is successful, exchanging a plurality of the target vouchers in the online mall; Step S1052, when settling offline shopping, automatically deducting a plurality of the target vouchers; Step S1053, after completing the settlement, obtain the points deduction data; Step S1054: update the online points data according to the points deduction data.

[0053] Furthermore, Figure 7 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0054] Among them, in another preferred embodiment provided by the present invention, the online shopping mall points redemption management system based on the points mechanism includes: The online tracking and recording unit 101 is used to obtain the service management authority of the target user, track and record the shopping browsing of the target user in the online mall, and obtain online browsing data and online points data.

[0055] In an embodiment of the present invention, the online tracking and recording unit 101 generates a permission application and sends the permission application to the mobile terminal of the target user. The target user can view the permission application on the mobile terminal, agree or reject the permission application and provide feedback. By receiving the application feedback from the mobile terminal of the target user, the application feedback is content identified. When the target user accepts the permission application, the service management authority of the target user is obtained. Based on the service management authority, the shopping browsing of the target user in the online mall is tracked and recorded to obtain online browsing data and online points data.

[0056] Specifically, Figure 8 It shows a structural block diagram of the online tracking and recording unit 101 in the system provided by an embodiment of the present invention.

[0057] In a preferred embodiment of the present invention, the online tracking and recording unit 101 specifically includes: The permission application module 1011 is used to generate and send a permission application to a target user; The feedback receiving module 1012 is used to receive the application feedback of the target user regarding the permission application; The permission acquisition module 1013 is used to acquire the service management permission of the target user according to the application feedback when the target user accepts the permission application; The tracking and recording module 1014 is used to track and record the shopping browsing of the target user in the online mall based on the service management authority, and obtain online browsing data and online points data.

[0058] Furthermore, the online shopping mall points redemption management system based on the points mechanism also includes: The interest analysis processing unit 102 is used to perform interest analysis on the online browsing data, determine a plurality of online interest commodities, and match the point vouchers corresponding to the plurality of online interest commodities according to the online point data.

[0059] In an embodiment of the present invention, the interest analysis processing unit 102 performs product analysis on the online browsing data to determine multiple online browsing products browsed by the target user in the online mall, and then performs time statistics analysis on the online browsing data based on the multiple online browsing products to obtain the browsing time of the multiple online browsing products, and performs frequency statistics analysis on the online browsing data to obtain the number of views of the multiple online browsing products, uses the multiple browsing time and the multiple browsing times as evaluation indicators, compares the interests of the multiple online browsing products, selects multiple online interest products, and analyzes the online points data based on a preset points mechanism to match the points vouchers corresponding to the multiple online interest products.

[0060] Specifically, Fig. 9 A structural block diagram of the interest analysis processing unit 102 in the system provided by an embodiment of the present invention is shown.

[0061] Among them, in the preferred embodiment provided by the present invention, the interest analysis processing unit 102 specifically includes: The commodity analysis module 1021 is used to perform commodity analysis on the online browsing data and determine a plurality of online browsing commodities; The duration statistics module 1022 is used to perform duration statistics analysis on the online browsing data to obtain the browsing duration of multiple online browsing products; The frequency statistics module 1023 is used to perform frequency statistics analysis on the online browsing data to obtain the number of views of the plurality of online browsed products; An interest comparison module 1024 is used to compare the interests of the plurality of online browsed products according to the plurality of browsing durations and the plurality of browsing times, and select a plurality of online interest products; The voucher matching module 1025 is used to analyze the online point data based on a preset point mechanism and match the point vouchers corresponding to the plurality of online interest products.

[0062] Furthermore, the online shopping mall points redemption management system based on the points mechanism also includes: The commodity settlement matching unit 103 is used to obtain offline settlement information when the user is shopping offline, and to perform commodity settlement matching based on the plurality of online commodities of interest to determine whether the matching is successful.

[0063] In an embodiment of the present invention, when a user performs offline shopping, the product settlement matching unit 103 obtains offline settlement information, identifies products based on the offline settlement information, determines multiple offline settlement products, and then matches the multiple offline settlement products based on multiple online interest products to determine whether the match is successful.

[0064] The multi-source verification judgment unit 104 is used to select multiple target interest commodities and multiple target vouchers when the matching is successful, and perform multi-source verification on the target user to determine whether the verification is successful.

[0065] In the embodiment of the present invention, when a match is possible, the multi-source verification judgment unit 104 selects a plurality of successfully matched target interest commodities from a plurality of online interest commodities, and then selects a plurality of target vouchers corresponding to the target interest commodities from a plurality of point vouchers. Thereafter, the target user is authenticated and the identity authentication result is recorded. The target user is then positionally verified and the position verification result is recorded. The target user is also subjected to relevant online and offline verification and the relevant verification results are recorded. Whether the verification is successful is determined by comprehensively analyzing the identity authentication result, the position verification result and the relevant verification results.

[0066] Specifically, Fig.10 It shows a structural block diagram of the multi-source verification judgment unit 104 in the system provided by an embodiment of the present invention.

[0067] Among them, in the preferred implementation mode provided by the present invention, the multi-source verification judgment unit 104 specifically includes: The product selection module 1041 is used to select a plurality of target interest products from the plurality of online interest products when the matching is successful; The voucher selection module 1042 is used to select target vouchers corresponding to multiple target interest commodities from the multiple point vouchers; The identity authentication module 1043 is used to authenticate the target user and record the identity authentication result; The location verification module 1044 is used to verify the location of the target user and record the location verification result; The relevant verification module 1045 is used to perform relevant online and offline verification on the target user and record relevant verification results; The verification judgment module 1046 is used to comprehensively judge whether the verification is successful based on the identity verification result, the location verification result and the related verification result.

[0068] Furthermore, the online shopping mall points redemption management system based on the points mechanism also includes: The voucher deduction processing unit 105 is used to redeem multiple target vouchers when the verification is successful, automatically deduct multiple target vouchers during offline shopping settlement, and update the online points data.

[0069] In an embodiment of the present invention, when the verification is successful, the voucher deduction processing unit 105 redeems multiple target vouchers through the target user's points in the online mall, and then automatically deducts multiple target vouchers during offline shopping settlement, and obtains the points deduction data after the settlement is completed, and then synchronously updates the online points data based on the points deduction data.

[0070] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0071] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0072] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0073] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A point redemption management method for an online shopping mall based on a point mechanism, characterized in that: The method specifically comprises the following steps: Obtain the service management authority of the target user, track and record the target user's shopping browsing in the online mall, and obtain online browsing data and online points data; Performing interest analysis on the online browsing data to determine a plurality of online products of interest, and matching the plurality of point vouchers corresponding to the online products of interest according to the online point data; When the user is shopping offline, offline settlement information is obtained, and commodity settlement matching is performed based on the plurality of online commodities of interest to determine whether the matching is successful; When the match is successful, multiple target interest products and multiple target vouchers are selected, and multi-source verification is performed on the target user to determine whether the verification is successful; When the verification is successful, a plurality of the target vouchers are exchanged, and when the offline shopping is settled, the plurality of the target vouchers are automatically deducted, and the online points data is updated; The process of obtaining the service management authority of the target user, tracking and recording the target user's shopping browsing in the online mall, and obtaining online browsing data and online points data specifically includes the following steps: Generate and send permission requests to target users; Receive application feedback from the target user regarding the permission application; According to the application feedback, when the target user accepts the permission application, the service management permission of the target user is obtained; Based on the service management authority, the target user's shopping browsing in the online mall is tracked and recorded to obtain online browsing data and online points data.

2. The online shopping mall points exchange management method based on the points mechanism according to claim 1 is characterized in that: Tracking and recording the target user's online shopping experience and obtaining online browsing data and online points data specifically includes the following steps: When users browse the online store, the product ID, timestamp and browsing duration are recorded; Calculate the total browsing time of the target user by adding up the browsing time in all browsing records of the target user; Identify the target user’s peak browsing time by calculating the timestamps that appear most frequently in the user’s browsing data; If the target user has a corresponding browsing record, the user's total browsing time and peak browsing time are used as feature inputs, and the user's browsing pattern is classified using a clustering algorithm to obtain the user behavior clustering result; Perform Fourier transform on the browsing time of each browsing record, and compare the frequency components in the Fourier transform result with the browsing peak time as a reference to obtain the periodicity analysis result; The corresponding points are calculated and distributed to users based on the total browsing time, peak browsing time, user behavior clustering results and periodic analysis results.

3. The online shopping mall points exchange management method based on the points mechanism according to claim 2 is characterized in that: The performing interest analysis on the online browsing data, determining a plurality of online interest commodities, and matching the point vouchers corresponding to the plurality of online interest commodities according to the online point data specifically comprises the following steps: Performing commodity analysis on the online browsing data to determine a plurality of online browsing commodities; Performing a duration statistical analysis on the online browsing data to obtain the browsing duration of a plurality of online browsed products; Performing a frequency statistical analysis on the online browsing data to obtain the number of times a plurality of online browsed products are viewed; Comparing the interests of the plurality of online browsed commodities according to the plurality of browsing durations and the plurality of browsing times, and selecting a plurality of online interested commodities; Based on a preset points mechanism, the online points data is analyzed to match points vouchers corresponding to a plurality of online products of interest.

4. The online shopping mall points exchange management method based on the points mechanism according to claim 3 is characterized in that: According to the plurality of browsing durations and the plurality of browsing times, performing interest comparison on the plurality of online browsing products and selecting a plurality of online interest products specifically comprises the following steps: Obtain multiple browsing durations and multiple browsing times, and determine the median values ​​corresponding to the browsing durations and browsing times; If the browsing time and browsing times are greater than the corresponding median value, a value of 1 is assigned; if it is less than the corresponding median value, the browsing time and browsing times are standardized to between [0,1] to obtain the fuzzy logic membership value of the browsing time and browsing times; According to the deviation of the user's browsing time and browsing times from the median, a smoothing function is used to calculate the adaptive weight; Perform weighted aggregation on the fuzzy logic membership values ​​of the browsing time and browsing times and the corresponding adaptive weights to obtain an aggregation result, and divide the aggregation result by the sum of the adaptive weights to obtain a comprehensive interest score; The comprehensive interest score is normalized using softmax to obtain the probability distribution, and online interest products are selected based on the probability distribution.

5. The online shopping mall points exchange management method based on the points mechanism according to claim 4 is characterized in that: When the user performs offline shopping, offline settlement information is obtained, and commodity settlement matching is performed based on the plurality of online commodities of interest, and determining whether the matching is successful specifically includes the following steps: When users make offline purchases, obtain offline settlement information; Perform commodity identification on the offline settlement information to determine multiple offline settlement commodities; Based on the multiple online interest products, the multiple offline settlement products are matched to determine whether the matching is successful.

6. The online shopping mall points exchange management method based on the points mechanism according to claim 5 is characterized in that: Based on the multiple online interest products, the multiple offline settlement products are matched, and judging whether the matching is successful specifically includes the following steps: The features of the online interest products and offline settlement products are converted into feature vectors in numerical form by word embedding, so as to obtain multiple feature vectors for each online interest product and offline settlement product; wherein the features of the online interest products and offline settlement products include name, category, and price; Assign weights to multiple feature vectors respectively, calculate the cosine similarity of each feature vector between the online interest products and the offline settlement products, and multiply the cosine similarity of each feature vector by the corresponding weight to obtain the contribution of the corresponding feature; The contribution of multiple features is accumulated to obtain the total similarity score of the product pair; A matching threshold is set, and product pairs with a total similarity score higher than the matching threshold are defined as successfully matched product pairs.

7. The online shopping mall points exchange management method based on the points mechanism according to claim 6 is characterized in that: When the matching is successful, multiple target interest commodities and multiple target vouchers are selected, and multi-source verification is performed on the target user. The determination of whether the verification is successful specifically includes the following steps: When the match is successful, selecting a plurality of target interest products from the plurality of online interest products; Selecting target vouchers corresponding to multiple target interest commodities from the multiple point vouchers; Authenticate the target user and record the authentication result; Perform location verification on the target user and record the location verification result; Conduct relevant online and offline verification of target users and record relevant verification results; The identity verification result, the location verification result and the related verification result are comprehensively considered to determine whether the verification is successful.

8. The online shopping mall points exchange management method based on the points mechanism according to claim 7 is characterized in that: Based on the identity verification result, the location verification result and the related verification result, determining whether the verification is successful specifically includes the following steps: Map the identity verification result, location verification result, and related verification result to a score between 0 and 1 to obtain an identity verification score, a location verification score, and a related verification score; Based on the user's historical behavior data, the conditional probability of identity verification is calculated. When the identity verification result is known, the conditional probability of location verification is calculated. Based on the result of location verification, the conditional probability of related verification is calculated. Multiply the conditional probability of identity verification, the conditional probability of location verification, and the conditional probability of correlation verification to get the joint probability; According to the periodic fluctuations of user browsing over time in history, the identity verification score, location verification score and related verification score are given time dynamic weights, and then weighted sum calculation is performed to obtain a preliminary comprehensive score; Given a verification threshold, the preliminary comprehensive score is multiplied by the joint probability to obtain the final comprehensive score, and then the final comprehensive score is compared with the verification threshold to determine whether the verification is successful.

9. The online shopping mall points exchange management method based on the points mechanism according to claim 8 is characterized in that: When the verification is successful, exchanging multiple target vouchers, automatically deducting multiple target vouchers during offline shopping settlement, and updating the online points data specifically include the following steps: When the verification is successful, redeem multiple target vouchers in the online mall; When settling offline purchases, multiple target vouchers are automatically deducted; After completing the settlement, obtain the points deduction data; The online points data is updated according to the points deduction data.

10. An online shopping mall points exchange management system based on a points mechanism, the system is applied to the online shopping mall points exchange management method based on a points mechanism as claimed in any one of claims 1 to 9, characterized in that: The system includes an online tracking and recording unit, an interest analysis processing unit, a commodity settlement matching unit, a multi-source verification and judgment unit, and a voucher deduction processing unit, wherein: The online tracking and recording unit is used to obtain the service management authority of the target user, track and record the target user's shopping browsing in the online mall, and obtain online browsing data and online points data; An interest analysis processing unit, configured to perform interest analysis on the online browsing data, determine a plurality of online interest commodities, and match a plurality of point vouchers corresponding to the online interest commodities according to the online point data; A commodity settlement matching unit, used to obtain offline settlement information when the user is shopping offline, and to match the commodity settlement based on the plurality of online commodities of interest, and to determine whether the matching is successful; A multi-source verification judgment unit is used to select multiple target interest commodities and multiple target vouchers when the match is successful, and perform multi-source verification on the target user to determine whether the verification is successful; The voucher deduction processing unit is used to redeem multiple target vouchers when the verification is successful, automatically deduct multiple target vouchers when settling offline shopping, and update the online points data.

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