Method for realizing unique identification of consumer identity based on space-time correspondence principle

Abstract

The invention relates to the technical field of big data analysis, in particular to a method for realizing unique identification of consumer identity based on a space-time correspondence principle. According to the invention, the consumption time and the consumption address field of the order database of the shop management system are integrated and aligned with the code scanning time and the base station coverage range field of the signaling database of the communication operator, so that the unique identification corresponding problem of the consumer identity is solved; according to the invention, through consumption behavior big data analysis and inter-industry data interaction and analytical calculation, an effective means of accurate identification of consumer identity for an order of completing collection by scanning a personal collection code is realized, the actual consumption condition of the consumer can be truly reflected, and the availability of overall consumption data is improved; by establishing the consumer information database, accurate correspondence of respective consumer identity information fields among current mainstream aggregation payment systems (WeChat, Alipay, cloud quick pass and Huawean PAY) is realized, and a bridge link is established for data interaction among industries.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and in particular to a method for realizing unique identification of consumer identities based on the principle of time-space correspondence. Background Art

[0002] Mobile payment, also known as mobile phone payment, is a service method that allows consumers to use mobile terminals such as mobile phones to pay for the goods or services they consume. The aggregate payment system effectively combines the Internet, terminal equipment, and financial institutions to realize the cashier function, providing consumers with financial services such as monetary payment and bill payment. There are many types of aggregate payment systems currently providing mobile payment services, and the mainstream systems include WeChat, Alipay, Cloud QuickPass, Huawei PAY, etc.; in the above-mentioned aggregate payment systems, each system has a different identification for consumers who complete the payment, such as WeChat uses the openID and Sub_openID field identification, and Alipay uses the Buy_user_ID field identification, which has resulted in the current situation where aggregate payment systems are everywhere, and the data between the aggregate payment systems cannot be interconnected.

[0003] Chinese patent document CN116664120A discloses "a method and system for realizing unique identification of consumer identity across payment channels", which uses the mobile phone number bound to WeChat users and the mobile phone number bound to Alipay users to build an associated primary key for WeChat Sub_openID and Alipay Buy_user_ID, and makes the unique identification ID of consumers independently fed back by WeChat and Alipay correspond one by one, thus realizing unique identification of consumer identity across WeChat and Alipay payment channels. The shortcomings of the existing technology are mainly the following two points:

[0004] 1. Only when the consumer agrees to provide the mobile phone number bound to the WeChat user and the mobile phone number bound to the Alipay user, can the unique identification of the consumer's identity be achieved across WeChat and Alipay. The application scope is small and the limitations are large;

[0005] 2. It only discloses the method of integrating the unique identification of consumers in the two payment channels of WeChat and Alipay, but cannot solve the problem of uniformly identifying the identity of consumers across payment channels currently in use on the market, such as Cloud QuickPass and Huawei Pay.

[0006] In addition, from the consumption data statistics of Shandong Province that apply the CN116664120A unified ID technology, it can be seen that the number of scan code payments completed through the store management system accounts for about 30% of the total number of scan code payments, and the amount of scan code payments completed through the store management system accounts for about 22% of the total scan code payment amount. The reason for the low proportion is that due to the problem of scan code handling fees, merchant retail terminals are unwilling to collect payments through the cashier channels that come with the store management system terminals. Merchants are more likely to collect payments by posting personal static payment codes in stores. Therefore, 70% of the current total scan code payment orders cannot achieve unified consumer identity identification, that is, the current validity of credible consumer behavior data is less than 80%, and the overall consumption data availability and analyzability are seriously insufficient. It cannot truly reflect the actual consumption of consumers and is insufficient to support the development of consumer portraits, consumer behavior research and market status monitoring. The fundamental reason is the lack of effective means to accurately identify the identity of consumers for orders that scan personal static payment codes to complete payment collection. Summary of the invention

[0007] Technical purpose: In order to overcome the shortcomings of the prior art, the present invention provides a method for realizing unique identification of consumer identities based on the principle of time-space correspondence. Through big data analysis of consumer behavior and data interaction between industries, the consumption time and consumption address fields of the store management system order database are integrated and aligned with the scanning time and base station coverage range fields of the communication operator signaling database, thereby solving the problem of unique identification of consumer identities. The technical solution of the present invention is as follows:

[0008] The present invention provides a method for realizing unique identification of consumer identity based on the principle of time-space correspondence, wherein data is exchanged between a store management system order database and a communication operator signaling database, a unique correspondence between a "consumer identification" field in the store management system order database and a "payment operation completed mobile phone number" field in the communication operator signaling database is established, and the unique correspondence is recorded in a consumer information database; the method comprises:

[0009] [S1] Initialization of the store management system order database data: Check whether the "Association_completion" field exists in the store management system order database; if it does not exist, create the "Association_completion" field and keep its field value NULL, and jump to the process to start a new cycle; if it exists, determine whether the "Consumer ID" in the store management system order database is NULL;

[0010] [S2] Integration of store management system order data with consumer identification and communication operator signaling data: If the "consumer identification" corresponding to the order data in the store management system order database is not NULL, the store management system order data with consumer identification and the communication operator signaling data are screened and aligned in the time dimension and space dimension, including:

[0011] [S2.1] Extraction of order data from the store management system with consumer identification: Extract the n1 "Order Number PurchaseOrder" field, the "PayTime" field for scan code payment, and the "Consumption_address" field data corresponding to any "Consumer Identification ID_identification" field data whose "Related Field" is NULL and the "Consumer Identification" field is not NULL, expressed as {(ID_identification label_1 、PurchaseOrder label_1 、PayTime label_1 、Consumption_address label_1 ), (ID_identification label_1 、PurchaseOrder label_2 、PayTime label_2 、Consumption_address label_2 ),...,(ID_identificationl abel_1 、PurchaseOrder label_n1 、PayTime label_n1 、Consumption_address label_n1 )}; the measurement unit of the “PayTime” is “milliseconds”, and the “Consumption_address” is a combination of a set of longitude and latitude numbers;

[0012] [S2.2] Perform multiple rounds of spatiotemporal data integration and alignment on the store management system order data with consumer identification: Use the "Consumption_address" field and "Consumption time PayTime" field data of the store management system order data obtained in step [S2.1] as the search primary key, and align and match them with the "Base station coverage range Csp_address" field and "Scan code time CspTime" field data in the communication operator signaling database one by one, and search for the set of mobile phone numbers whose "Consumption address Consumption_address" is within the "Base station coverage range Csp_address" and whose "Consumption time PayTime" and "Scan code time CspTime" are in the same time period, that is, the set of all mobile phone numbers that have opened the mobile payment software in the Consumption_address address and PayTime time period, recorded as {PhoneNumber_CSP label};

[0013] In the first round of search, using formula 2.2.1 as the search condition, the search result {PhoneNumber_CSP label_1};

[0014] (Consumption_address label_1 ∈Csp_addressl abel_1 )∩[(PayTime label_1 -T_Delay_label)≤CspTime label_1 <PayTime label_1 ] Formula 2.2.1;

[0015] In the second round of search, using formula 2.2.2 as the search condition, the search result {PhoneNumber_CSP label_2};

[0016] (Consumption_address label_2 ∈Csp_address label_2 )N[(PayTimel label_2 -T_Delay_label)≤CspTime label_2 <PayTime label_2 ] Formula 2.2.2;

[0017] …

[0018] In the n2th round of search, the search result {PhoneNumber_CSP label_n2};

[0019] (Consumption_address label_n2 ∈Csp_address label_n2 )∩[(PayTime label_n2 -T_Delay_label)≤CspTime label_n2 <PayTime labei_n2 ]Formula 2.2.n2;

[0020] Among them, T_Delay_label≤300000, n2≥1, n1≥n2;

[0021] [S2.3] Intersection of multiple rounds of search results: Intersection of the n2 sets of mobile phone numbers obtained in step [S2.2] is taken, as shown in formula 2.3.1, until the result of the operation is a single data set;

[0022] PhoneNumber_CSP label_end ={PhoneNumber_CSP label_1}∩{PhoneNumber_CSP label_2}∩......∩{PhoneNumber_CSP label_n2}; Formula 2.3.1

[0023] Through the above steps, establish the "Consumer ID_identification label_1 " and " implement scanning operation mobile phone number PhoneNumber_CSP label_end " unique correspondence; the "consumer identification ID_identification label_1 " is recorded in the "Consumer ID_consumer" field of the consumer information database, and the "Scanning operation mobile phone number PhoneNumber_CSP label_end " is recorded in the "Consumer mobile phone number Phone_consumer" field of the consumer information database;

[0024] [S2.4] Loop through the store management system order database A: In the store management system order database, use formula 2.4.1 as the search primary key and assign the value PhoneNumber_CSP to the search result column "Complete payment operation mobile phone number PhoneNumber" label_end , the "Association_completion" field is assigned a value of "1";

[0025] (Consumer ID = ID_identification label_1)∩(association completed=NULL) Formula 2.4.1

[0026] [S2.5] Perform round B of traversal loop on the store management system order database: In the store management system order database, execute steps [S2.1]-[S2.4] in sequence on the store management system order data with consumer identification, so as to achieve accurate correspondence between the "Mobile phone number PhoneNumber_CSP used to implement the scanning operation" field in the communication operator signaling database and the "Consumer identification ID_identification" field in the store management system order database.

[0027] Furthermore, in step [S2.2], T_Delay_label=120000.

[0028] Furthermore, in step [S2.2], n2=6.

[0029] Furthermore, the step [S3] is also included to integrate the store management system order data without consumer identification with the communication operator signaling data, that is, using the image information contained in the personal static payment code posted by the merchant store as the identification primary key, the store management system order data without consumer identification and the communication operator signaling data are subjected to a single round of data screening and alignment in the time dimension and the space dimension:

[0030] [S3.1] Extraction of order data from store management systems without consumer identification: Extract the merchant's "Photo Shop Pic_pay" field and the corresponding "Order Number PurchaseOrder" field, "Consumption Time PayTime" field, and "Consumption Address Consumption_address" field data from any store management system order data where the consumer completes payment using the personal static payment code posted by the store and the "Consumer Identification" field is NULL, expressed as (Pic_pay unlabel_1 、PurchaseOrder unlabel_1 、PayTime unlabel_1 、Consumption_address unlabel_1 ); the measurement unit of the “PayTime” is “milliseconds”, and the “Consumption_address” is a combination of a set of longitude and latitude numbers;

[0031] [S3.2] Perform a single-round spatiotemporal data alignment on the store management system order data without consumer identification: Use the "Consumption address Consumption_address" field and "Consumption time PayTime" field data of the store management system order data obtained in step [S3.1] as the search primary key, and align and match them with the "Base station coverage range Csp_address" field and "Scanning code time CspTime" field data in the communication operator's signaling database one by one, and search for the set of mobile phone numbers whose "Consumption address Consumption_address" is within the "Base station coverage range Csp_address" and whose "Consumption time PayTime" and "Scanning code time CspTime" are in the same time period. That is, use Formula 3.2.1 as the search condition, and the search result is the set of "Mobile phone numbers PhoneNumber_CSP that perform scanning operations", recorded as {PhoneNumber_CSP unlabel};

[0032] (Consumption_address unlabel ∈Csp_address unlabei )∩[(PayTime unlabel -T_Delay_unlabel)≤CspTime unlabel ≤(PayTime unlabel +T_Delay_unlabel)] Formula 3.2.1;

[0033] Among them, T_Delay_unlabel≤300000;

[0034] [S3.3] Align the avatar data of the store management system order data without consumer identification: Use the "avatar photo store Pic_pay" field data in step [S3.1] as the identification primary key, and the "scanning operation mobile phone number" set {PhoneNumber_CSP unlabel}The corresponding communication operator signaling database records the merchant's "Avatar Photo Operator Pic_CSP" field data for image data alignment and matching;

[0035] [S3.4] Determination of the result of the portrait data integration alignment: If the picture data alignment matching result in step [S3.3] is a single identity {Pic_pay only1 =Pic_CSP only1}, that is, find the consumption_address only1 Address, PayTime only1The unique merchant personal static payment code that completes the payment in the time period, and can find the corresponding Csp_address only1 Address, CspTime only1 The unique mobile phone number that has opened the mobile app to complete the payment operation during the time period, and then determine the merchant's "Avatar Photo Store Pic_pay" in the order data of the store management system only1 "The corresponding order number PurchaseOrder only1 "With the merchant in the communication operator's signaling database" avatar photo store Pic_CSP only1 "Corresponding to "Scan operation mobile phone number PhoneNumber_CSP only1 "There is a unique correspondence;

[0036] [S3.5] Update the order data of the store management system without the consumer ID: perform the scanning operation of the mobile phone number PhoneNumber_CSP as described in step [S3.4] only1 " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP only1 =Phone_consumer only1 , then PhoneNumber_CSP only1 It has been recorded in the consumer information database, so the consumer's mobile phone number can be obtained. only1 "Consumer ID_consumer only1 "; store management system "order number PurchaseOrder only1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value "PhoneNumber_CSP only1 ", the store management system "Order No. PurchaseOrder only1 "The corresponding "Consumer Identification ID_identification" field is assigned the value "ID_consumer only1 ", the store management system "Order No. PurchaseOrder only1 "The corresponding "Association_completion" field is assigned a value of "1";

[0037] [S3.6] Perform C-round traversal loop on the store management system order database: In the store management system order database, perform steps [S3.1]-[S3.5] in sequence on the store management system order data without consumer identification, and integrate the store management system order data without consumer identification with the communication operator's signaling data, thereby identifying and filling in the "Consumer Identification ID_identification" and "Phone Number for completing payment operation" fields of the store management system order data without consumer identification, thereby achieving accurate identification of the consumer identity of the store management system order data without consumer identification.

[0038] Furthermore, the personal static payment code posted by the store in step [S3.1] includes: the merchant's WeChat, Alipay, UnionPay, Huawei PAY and other personal static payment codes provided by other mobile payment service providers.

[0039] Furthermore, in step [S3.2], T_Delay_unlabel=120000.

[0040] Furthermore, if the picture data alignment matching result in step [S3.3] is a non-unique identity set, it is recorded as {Pic_pay non_uniqueness_1 =Pic_CSP non_uniqueness_1 =Pic_CSP non_uniqueness_2 =......=Pic_CSP non_uniqueness_n3}, which means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 There are multiple merchants with personal static payment codes in the time period to complete the payment operation;

[0041] [S3.7] Extract the mobile phone number data for the scanning operation: Extract the identity set {Pic_pay non_uniqueness_1 =Pic_CSP non_uniqueness_1 =Pic_CSP non_uniqueness_2 =......=Pic_CSP non_uniqueness_n3} The picture information data contained in the merchant's personal static payment code {Pic_CSP non_uniqueness_1 、Pic_CSP non_uniqueness_2 , ..., Pic_CSP non_uniqueness_n3}, query the communication operator's signaling database for the "scanning operation mobile phone number" set corresponding to the image information data contained in the merchant's personal static payment code {PhoneNumber_CSP non_uniqueness_1 、PhoneNumber_CSP non_uniqueness_2 , ..., PhoneNumber_CSP non_uniqueness_n3}, so as to get the corresponding consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Multiple mobile phone numbers that have opened the mobile app to complete payment operations during a certain period of time; query the merchant's "Avatar Photo Store Pic_pay" in the order data of the store management system non_uniqueness_1 "The corresponding order number PurchaseOrder non_uniqueness_1 ”;

[0042] [S3.8] Identify the consumer's identity through historical behavior characteristics: Use the consumer's behavior habits as the identification primary key to finely identify the set of "mobile phone numbers used to perform scanning operations" described in step [S3.7], thereby achieving unique identification of the consumer's identity.

[0043] Furthermore, in step [S3.8], the consumer identity is identified by historical behavior characteristics:

[0044] [S3.8.1] Use the historical “consumption frequency” as the first matching condition to identify consumer behavior habits;

[0045] [S3.8.1.1] Extract the historical "consumption times" data corresponding to the mobile phone number that performs the scanning operation: Take the "scanning operation mobile phone number" set {PhoneNumber_CSP non_uniqueness_1 、PhoneNumber_CSP non_uniqueness_2 ,......,PhoneNumber_CSP non_uniqueness_n3} any one of "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_1 " is the search value, and the "Mobile phone number PhoneNumber_CSP for implementing the scanning operation" is queried from the store management system order database. non_uniqueness_1 "Consumption_address non_uniqueness_1 Address" historical "consumption frequency Frequency_address non_uniqueness_1 ”;

[0046] [S3.8.1.2] In the store management system order database, the set of "scanning operation mobile phone numbers" {PhoneNumber_CSP non_uniqueness_1 、PhoneNumber_CSP non_uniqueness_2 ,......,PhoneNumber_CSP non_uniqueness_n3} executes step [S3.8.1.1] to traverse the loop operation, thereby obtaining all elements in the "scanning operation mobile phone number" set in "Consumption_address non_uniqueness_1 The historical "consumption frequency" collection of "address" {Frequency_address non_uniqueness_1 、Frequency_address non_uniqueness_2 、……、Frequency_address non_uniqueness_n3};

[0047] [S3.8.1.3] If there is a unique maximum value Frequency_address in the historical "consumption times" set described in step [S3.8.1.2] non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Frequency_address non_uniqueness_max Corresponding to "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_address_max "Most often in Consumption_address non_uniqueness_1 address store consumption, and thus infer the merchant's "avatar photo store Pic_pay non_uniqueness_1 "The corresponding order number PurchaseOrder non_uniqueness_1 "With the merchant in the communication operator's signaling database" avatar photo operator Pic_CSP non_uniqueness_address_max "Corresponding to "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_address_max "There is a unique correspondence;

[0048] [S3.8.1.4] Perform the scanning operation for the mobile phone number PhoneNumber_CSP as described in step [S3.8.1.3] non_uniqueness_address_max " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP non_uniqueness_address_max =Phone_consumer non_uniqueness_address_max , then PhoneNumber_CSP non_uniqueness_address _ max It has been recorded in the consumer information database, so the consumer's mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_address_max"Consumer ID_consumer non_uniqueness_address_max ”;

[0049] [S3.8.1.5] In the store management system, enter the “PurchaseOrder non_uniqueness_1 "The corresponding "Consumer Identification ID_identification" field is assigned the value ID_consumer non_uniqueness_address_max ; Change the order number to PurchaseOrder non_uniqueness_1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value PhoneNumber_CSP non_uniquenessaddress_max ; Change the order number to PurchaseOrder non_uniqueness_max "The corresponding "Association_completion" field is assigned a value of "1";

[0050] [S3.8.2] Use the historical "consumption commodity type" as the second matching condition to identify consumer behavior habits; if there are two or more identical maximum values ​​of Frequency_address in the historical "consumption frequency" set in step [S3.8.1.3] non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Among the multiple mobile phone numbers that have opened the mobile app to complete payment operations during the period, there are two or more consumers who often meet the consumption_address non_uniqueness_1 The first matching condition for address store consumption;

[0051] [S3.8.2.1] Extract the historical "consumed goods category" data corresponding to the mobile phone number that performed the scanning operation: In the store management system order data, query the "order number PurchaseOrder" mentioned in step [S3.7] non_uniqueness_1 "Consumer Goods Category" non_uniqueness_1 ”;

[0052] [S3.8.2.2] Extract the set of mobile phone numbers that implement scanning operations corresponding to the maximum value of "consumption times": In the store management system order database, extract the set of mobile phone numbers that implement scanning operations corresponding to the maximum value of the historical "consumption times" described in step [S3.8.2], recorded as {PhoneNumber_CSP non_uniqueness_address_1 , ..., PhoneNumber_CSP non_uniqueness_address_n4};

[0053] [S3.8.2.3] Calculate the historical consumption times corresponding to the mobile phone number that completed the payment operation corresponding to the maximum value of "consumption times": From any "scanning operation mobile phone number PhoneNumber_CSP" in the set of mobile phone numbers that performed the scanning operation corresponding to the maximum value of the historical "consumption times" in step [S3.8.2.2] non_uniqueness_address_1 " is the search value, and PhoneNumber_CSP is queried from the store management system order database non_uniqueness_address_1 Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1 The historical consumption frequency of the product, recorded as Frequency_category non_uniqueness_1 ;

[0054] [S3.8.2.4] In the store management system order database, perform the traversal loop operation of step [S3.8.2.3] for all elements in the set of mobile phone numbers for scanning operations corresponding to the maximum value of the historical "consumption times" in step [S3.8.2.2], so as to obtain all elements in the set of mobile phone numbers for scanning operations corresponding to the maximum value of the historical "consumption times" in step [S3.8.2.2] in Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1 The historical consumption frequency of a product is recorded as {Frequency_category non_uniqueness_1 ,...,Frequency_category non_uniqueness_n4};

[0055] [S3.8.2.5] If step [S3.8.2.4] purchases Category non_uniqueness_1 There is a unique maximum value Frequency_category in the historical consumption frequency set of the product non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Frequency_category non_uniqueness_max Corresponding to "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_category_max "Most often in Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1 Therefore, it is inferred that the merchant's "avatar photo store Pic_pay" in the store management system order data non_uniqueness_1"The corresponding order number PurchaseOrder non_uniqueness_1 "With the merchant in the communication operator's signaling database" avatar photo operator Pic_CSP non_uniqueness_category_max "Corresponding to "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_category_max "There is a unique correspondence;

[0056] [S3.8.2.6] Perform the scanning operation for the mobile phone number PhoneNumber_CSP as described in step [S3.8.2.5] non_uniqueness_category_max " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP non_uniqueness_category_max =Phone_consumer non_uniqueness_category_max , then PhoneNumber_CSP non_uniqueness_category_max It has been recorded in the consumer information database, so the consumer's mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_category_max "Consumer ID_consumer non_uniqueness_category_max ”;

[0057] [S3.8.2.7] In the store management system, change the order number to PurchaseOrder non_uniqueness_1 "The corresponding "Consumer Identification ID_identification" field is assigned the value ID_consumer non_unlqueness_category_max ; Change the order number to PurchaseOrder non_uniqueness_1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value PhoneNumber_CSP non_uniqueness_category_max ; Change the order number to PurchaseOrder non_uniqueness_1 "The corresponding "Association_completion" field is assigned a value of "1";

[0058] [S3.8.3] Use historical "consumption time" as the third matching condition to identify consumer behavior habits; if the purchase category in step [S3.8.2.4] non_uniqueness_1 There are two or more identical maximum values ​​of Frequency_category in the historical consumption frequency set of the product non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1Among multiple mobile phone numbers that have opened the mobile app to complete payment operations during the period, two or more consumers meet the "frequent consumption_address non_uniqueness_1 The first matching condition of address store consumption" and "frequently purchased Category" non_uniqueness_1 The second matching condition of the product";

[0059] [S3.8.3.1] Extract the historical "consumption time" data corresponding to the mobile phone number that performed the scanning operation: In the store management system order data, query the "order number PurchaseOrder" mentioned in step [S3.7] non_uniqueness_1 "The corresponding "PayTime non_uniqueness_1 "; Divide the 24 hours of a day into m time periods, and find the "PayTime non_uniqueness_1 "The corresponding time period is recorded as "Order Time Period Timesplit non_uniqueness_1 ”;

[0060] [S3.8.3.2] Extract the set of mobile phone numbers that perform scanning operations and correspond to the data that meets the first and second matching conditions: In the store management system order database, extract the mobile phone numbers that meet the requirements of "frequently in Consumption_address" in step [S3.8.3] non_uniqueness_1 The first matching condition for address store consumption is "frequently purchased Category" non_uniqueness_1 The set of mobile phone numbers for scanning operations corresponding to the second matching condition of the product is recorded as {PhoneNumber_CSP non_uniqueness_time_1 ,......,PhoneNumber_CSP non_uniqueness_time_n5};

[0061] [S3.8.3.3] Calculate the "scanning time CspTime" corresponding to the mobile phone number that performs the scanning operation corresponding to the data that meets the first and second matching conditions, which belongs to the "order time period Timesplit" in step [S3.8.3.1] non_uniqueness_1 " times; from step [S3.8.3.2] {PhoneNumber_CSP non_uniqueness_time_1 ,......,PhoneNumber_CSP non_uniqueness_time_n5} collection, select any one of the "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_time_1 " is the search value, and PhoneNumber_CSP is queried from the store management system order database non_uniqueness_time_1 Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1The "scanning time CspTime" corresponding to the product non_uniqueness_time_1 " belongs to the "Order Time Period Timesplit" described in step [S3.8.3.1] non_uniqueness_1 "Time, recorded as Frequency_time non_uniqueness_1 ;

[0062] [S3.8.3.4] In the store management system order database, the {PhoneNumber_CSP non_uniqueness_time_1 ,......,PhoneNumber_CSP non_uniqueness_time_n5}Execute step [S3.8.3.3] to loop through all elements in the collection, and obtain the non_uniqueness_1 Address, Purchase Category non_uniqueness_1 The "scanning time CspTime" corresponding to the product non_uniqueness_time " belongs to the "Order Time Period Timesplit" described in step [S3.8.3.1] non_uniqueness_1 "Frequency_time non_uniqueness_1 , ..., Frequency_time non_uniqueness_n5};

[0063] [S3.8.3.5] If the number set {Frequency_time non_uniqueness_1 ,......,Frequency_time non_uniqueness_n5 There is a unique maximum value Frequency_time in} non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Frequency_time non_uniqueness_max Corresponding to "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_time_max "Most often in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Time to buy Category non_uniqueness_1 Therefore, it is inferred that the merchant's "avatar photo store Pic_pay" in the store management system order data non_uniqueness_1 "The corresponding order number PurchaseOrder non_uniqueness_1 "With the merchant in the communication operator's signaling database" avatar photo operator Pic_CSP non_uniqueness _timemax "Corresponding to "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_time_max "There is a unique correspondence;

[0064] [S3.8.3.6] Perform the scanning operation for the mobile phone number PhoneNumber_CSP as described in step [S3.8.3.5] non_uniqueness_time_max " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP non_uniqueness_time_max =Phone_consumer non_uniqueness_time_max , then PhoneNumber_CSP non_uniqueness_time_max It has been recorded in the consumer information database, so the consumer's mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_time_max "Consumer ID_consumer non_uniqueness_time_max ”;

[0065] [S3.8.3.7] In the store management system, set the "Order Number PurchaseOrder non_uniqueness_1 "Consumer ID" _ The identification" field is assigned the value ID_consumer non_uniqueness_time_max ; Change the order number to PurchaseOrder non_uniqueness_1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value PhoneNumber_CSP non_uniqueness_time_max ; Change the order number to PurchaseOrder non_uniqueness_1 "The corresponding "Association_completion" field is assigned a value of "1";

[0066] With the historical "number of consumption times" as the first matching condition, the historical "type of goods consumed" as the second matching condition, and the historical "consumption time" as the third matching condition, through the three-layer progressive matching form, consumer behavior habits are used as the primary identification key to achieve fine identification of the "mobile phone number that performs scanning operations" collection.

[0067] Furthermore, in step [S3.8.3.1], m=24.

[0068] Furthermore, [S2.3] the consumer information database also includes the fields of "Consumer Identification UnionPay_consumer" and "Consumer Identification HuaweiPay_consumer", with the mobile phone number registered for UnionPay and Huawei PAY as the associated primary key, to achieve the associated identification of the same consumer's "Consumer Mobile Phone Number Phone_consumer", "Consumer Number ID_consumer", "Consumer Identification_UnionPay_consumer" and "Consumer Identification_HuaweiPay_consumer" field data.

[0069] The beneficial effects of the present invention are:

[0070] 1. The present invention provides a method for realizing unique identification of consumer identities based on the principle of time-space correspondence, which solves the problem of unique identification of consumer identities by integrating and aligning the consumption time and consumption address fields of the store management system order database with the scanning time and base station coverage range fields of the communication operator signaling database;

[0071] 2. The present invention provides a method for uniquely identifying a consumer's identity based on the principle of time-space correspondence, which provides an effective means for accurately identifying the consumer's identity for orders that complete payment by scanning a personal static payment code. It can truly reflect the actual consumption of consumers, improve the availability of overall consumption data, and provide data support for conducting consumer portraits, consumer behavior research, and market status monitoring;

[0072] 3. The present invention provides a method for uniquely identifying a consumer based on the principle of time-space correspondence. The method realizes unique identification of a consumer through big data analysis of consumer behavior and data interaction and analytical calculation between industries. Consumers no longer need to authorize their mobile phone numbers to WeChat mini programs or Alipay mini programs, which provides good user experience and wide application range.

[0073] 4. The present invention provides a method for realizing unique identification of consumer identity based on the principle of time-space correspondence. By establishing a consumer information database, the precise correspondence between the consumer identity information fields of the current mainstream aggregated payment systems (WeChat, Alipay, Cloud QuickPass, Huawei PAY) is achieved, building a bridge for data interaction between industries. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0075] Figure 1 It is a method for realizing unique identification of consumer identity based on the principle of time-space correspondence. The flowchart of the "Consumer Identification" part;

[0076] Figure 2 It is a method for realizing unique identification of consumer identity based on the principle of time-space correspondence. Partial flow chart of "no consumer identification";

[0077] Figure 3 It is a general flow chart of a method for realizing unique identification of consumer identity based on the principle of time-space correspondence. DETAILED DESCRIPTION

[0078] The exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that the following description is only illustrative and exemplary in nature and is not intended to limit the present invention and its application or use. Unless otherwise specifically stated, the relative positions, numerical expressions and numerical values ​​of the components and steps described in the embodiments do not limit the scope of the present invention. In addition, techniques, methods and devices known to those skilled in the art may not be discussed in detail, but are intended to be part of the specification in appropriate circumstances.

[0079] The statistical tables of database field information of the embodiment of the present invention are shown in Table 1 to Table 3:

[0080] Table 1: Store management system order database field information table

[0081]

[0082]

[0083] Table 2: Communication operator signaling database field information table

[0084] Field Name English logo Base station coverage Csp_address Scan code time CspTime Scanning operation mobile phone number PhoneNumber_CSP Profile Photo_Operator Pic_CSP

[0085] Table 3: Consumer information database field information table

[0086] Field Name English logo Consumer Number ID_consumer Consumer mobile phone number Phone_consumer Consumer Logo_Cloud QuickPass UnionPay_consumer Consumer Logo_Huawei HuaweiPay_consumer

[0087] Embodiment 1 is a method for realizing unique identification of consumer identity based on the time-space correspondence principle disclosed by the present invention, which is applicable to order data of a store management system with consumer identification, such as Figure 1 As shown:

[0088] [S1] Initialization of the store management system order database data: Check whether the "Association_completion" field exists in the store management system order database shown in Table 1; if not, create the "Association_completion" field and keep its field value NULL; if it exists, jump to the next step;

[0089] The status of each database in step [S2] is shown in Table 4-Table 5:

[0090] Table 4: Step [S2] Details of some fields in the store management system order database

[0091]

[0092]

[0093] Table 5: Step [S2] Communication operator signaling database partial field data list

[0094]

[0095]

[0096] [S2] Integration of store management system order data with consumer identification and communication operator signaling data: If the "consumer identification" corresponding to the order data in the store management system order database is not NULL, the store management system order data with consumer identification and the communication operator signaling data are screened and aligned in the time dimension and space dimension, including:

[0097] [S2.1] Extraction of order data of the store management system with consumer identification: From the store management system order database shown in Table 4, extract the n1 "Order Number PurchaseOrder" field, the "PayTime" field for scan code payment, and the "Consumption_address" field data corresponding to any "Consumer Identification ID_identification" field data whose "Association Field" is NULL and the "Consumer Identification" field is not NULL, expressed as {(abcdef, 100001, 2024 / 2 / 2014: 48:04.62, 39°52'48″N 116°24′20″E), (abcdef, 100002, 2024 / 3 / 2014: 38:04.13, 39°52'48″N 116°24′20″E 116°24'20″E), (abcdef, 100003, 2024 / 4 / 2014: 45:04.89, 39°52'48″N116°24′20″E), (abcdef, 100004, 2024 / 5 / 2014: 39:04.31, 39°52'48″N 116°24'20″E)};

[0098] [S2.2] Perform multiple rounds of spatiotemporal data integration and alignment on the store management system order data with consumer identification: Use the "Consumption address Consumption_address" field and "Consumption time PayTime" field data of the store management system order data obtained in step [S2.1] as the search primary key, and align and match them one by one with the "Base station coverage range Csp_address" field and "Scan code time CspTime" field data in the communication operator signaling database shown in Table 2 and Table 5, and search for the set of mobile phone numbers whose "Consumption address Consumption_address" is within the "Base station coverage range Csp_address" and whose "Consumption time PayTime" and "Scan code time CspTime" are in the same time period, that is, the set of all mobile phone numbers that have opened the mobile payment software in the Consumption_address address and PayTime time period, recorded as {PhoneNumber_CSP label}; One thing needs to be explained here. Whether the base station coverage includes a certain latitude and longitude address is a prior art in the field of mobile communications. This patent applies the above prior art to determine the consumer address condition;

[0099] In the first round of search, using formula 2.2.1 as the search condition, the search results are {131****1111, 132****1111, 133****1111, 134****1111};

[0100] (Consumption_address label_1 ∈Csp_address label_1 )∩[(PayTime label_1 -120000)≤CspTime label_1 <PayTime label_1 ] Formula 2.2.1;

[0101] In the second round of search, using formula 2.2.2 as the search condition, the search results are {131****1111, 132****1111, 133****1111, 134****2222};

[0102] (Consumption_address label_2 ∈Csp_address label_2 )∩[(PayTimel label_2 -120000)≤CspTime label_2 <PayTime label_2 ] Formula 2.2.2;

[0103] In the third round of search, using formula 2.2.3 as the search condition, the search results are {131****1111, 132****1111, 133****3333, 134****3333};

[0104] (Consumption_address label_3 ∈Csp_address label_3 )∩[(PayTimel label_3 -120000)≤CspTime label_3 <PayTime label_3 ] Formula 2.2.3;

[0105] In the fourth round of search, using formula 2.2.4 as the search condition, the search results are {131****1111, 132****4444, 133****4444, 134****4444};

[0106] (Consumption_address label_4 ∈Csp_address label_4 )∩[(PayTimel label_4 -120000)≤CspTime label_4 <PayTime label_4 ] Formula 2.2.4;

[0107] [S2.3] Intersection of multiple rounds of search results: Intersect the four sets of mobile phone numbers obtained in step [S2.2], as shown in formula 2.3.1, until the result of the operation is a single data set {131****1111};

[0108] PhoneNumber_CSP label_end ={131****1111, 132****1111, 133****1111, 134****1111}∩{131****1111, 132****1111, 133****1111, 134****2222} n{131****1111, 132****1111, 133****3333, 134****3333}∩{131****1111, 132****4444, 133****4444, 134****4444}; Formula 2.3.1

[0109] Through the above steps, a unique correspondence between the "consumer identifier" abcdef and the "scanning operation mobile phone number" 131****1111 is established; the "consumer identifier" abcdef is recorded in the "consumer number ID_consumer" field of the consumer information database shown in Table 3, and the "scanning operation mobile phone number" 131****1111 is recorded in the "consumer mobile phone number Phone_consumer" field of the consumer information database;

[0110] [S2.4] Loop through round A of the store management system order database: In the store management system order database, use formula 2.4.1 as the search primary key, assign the value 131****1111 to the search result column "Completed payment operation mobile phone number PhoneNumber" and the value "1" to the "Association_completion" field;

[0111] (Consumer ID = abcdef)∩(Association completion = NULL) Formula 2.4.1

[0112] [S2.5] Perform round B of traversal loop on the store management system order database: In the store management system order database, execute steps [S2.1]-[S2.4] in sequence on the store management system order data with consumer identification, so as to achieve accurate correspondence between the "Mobile phone number PhoneNumber_CSP used to implement the scanning operation" field in the communication operator signaling database and the "Consumer identification ID_identification" field in the store management system order database.

[0113] Embodiment 2 is a method for realizing unique identification of consumer identity based on the time-space correspondence principle disclosed by the present invention, which is applicable to order data of a store management system without consumer identification, such as Figure 2 As shown:

[0114] The status of each database in step [S3] is shown in Table 6 to Table 15:

[0115] Table 6: Step [S3] Details of some fields in the store management system order database

[0116]

[0117] Table 7: Step [S3] Communication operator signaling database partial field data list

[0118]

[0119]

[0120]

[0121] Table 8: Step [S3] Consumer information database partial field data details

[0122] Consumer Number Consumer mobile phone number bbcdef 151****1111 cbcdef 181****2222

[0123] [S3] The order data of the store management system without consumer identification is integrated with the signaling data of the communication operator. That is, the image information contained in the personal static payment code posted by the merchant store is used as the identification primary key, and the order data of the store management system without consumer identification and the signaling data of the communication operator are screened and aligned in a single round in the time dimension and the space dimension:

[0124] [S3.1] Extraction of store management system order data without consumer identification: As shown in Table 6, the merchant's "Avatar Photo Store Pic_pay" field and the corresponding "Order Number PurchaseOrder" field, "Consumption Time PayTime" field, and "Consumption Address Consumption_address" field data are extracted from the store management system order data generated by the consumer using the merchant's WeChat and the "Consumer Identification" field is NULL, expressed as (store avatar 1, 200001, 2024 / 6 / 10 11:22:01.39, 39°52'48"N 116°24'20"E), (store avatar 2, 200002, 2024 / 7 / 10 11:22:01.39, 39°52'48"N 116°24'20"E);

[0125] [S3.2] Perform a single-round spatiotemporal data alignment on the store management system order data without consumer identification: Use the "Consumption address Consumption_address" field and "Consumption time PayTime" field data of the store management system order data obtained in step [S3.1] as the search primary key, and align and match them with the "Base station coverage range Csp_address" field and "Scanning code time CspTime" field data in the communication operator's signaling database one by one, and search for the set of mobile phone numbers whose "Consumption address Consumption_address" is within the "Base station coverage range Csp_address" and whose "Consumption time PayTime" and "Scanning code time CspTime" are in the same time period. That is, use Formula 3.2.1 as the search condition, and the search result is the set of "Mobile phone numbers PhoneNumber_CSP that perform scanning operations", recorded as {PhoneNumber_CSP unlabel};

[0126] (Consumption_address unlabel ∈Csp_address unlabel )∩[(PayTime unlabel -120000)≤CspTime unlabel ≤(PayTime unlabel +120000)] Formula 3.2.1;

[0127] As shown in Table 7, using Formula 3.2.1 as the search condition, the search results are as follows:

[0128] The search results corresponding to the order number 200001 data are: {151****1111, 152****1111, 153****1111};

[0129] The search results corresponding to the order number 200002 data are: {181****2222, 182****2222, 183****2222, 184****2222, 185****2222, 186****2222, 187****2222, 188****2222, 189****2222};

[0130] [S3.3] Align the avatar data of the store management system order data without consumer identification: Use the "avatar photo store Pic_pay" field data in step [S3.1] as the identification primary key, and the "scanning operation mobile phone number" set {PhoneNumber_CSP unlabel}The corresponding communication operator signaling database records the merchant's "Avatar Photo Operator Pic_CSP" field data for image data alignment and matching;

[0131] The alignment and matching result of the avatar photo of the order number 200001 data is: {store avatar 1 = operator avatar 11};

[0132] The alignment and matching result of the avatar photo of the order number 200002 data is: {Store avatar 2 = Operator avatar 21 = Operator avatar 22 = Operator avatar 23 = Operator avatar 28 =

[0133] Operator avatar 29};

[0134] [S3.4] Determination of the result of the portrait data integration alignment: If the picture data alignment matching result in step [S3.3] is a single identity {Pic_pay only1 =Pic_CSP only1}, corresponding to the order number 200001, that is, the unique merchant personal static payment code that completed the payment at the address of 39°52'48"N116°24'20″E and the time period of 2024 / 6 / 1011:22:01.39 is found, and the corresponding unique mobile phone number that opened the mobile software to complete the payment operation at the address of 39°52'48"N 116°24'20″E and the time period of 2024 / 6 / 1011:22:02.39 can be found, and then it is determined that the "order number 200001" corresponding to the merchant "store avatar 1" in the store management system order data and the "scanning operation mobile phone number 151****1111" corresponding to the merchant "operator avatar 11" in the communication operator signaling database have a unique corresponding relationship;

[0135] [S3.5] Update the order data of the store management system without consumer identification: as shown in Table 8, use the "scanning operation mobile phone number 151****1111" described in step [S3.4] as the search value, and search in the "consumer mobile phone number Phone_consumer" field data in the consumer information database described in step [S2.3]; if the search result is a unique match value, it means that 151****1111 has been recorded in the consumer information database, so that the "consumer number bbcdef" corresponding to the "consumer mobile phone number 151****1111" can be obtained; assign "151****1111" to the "payment operation mobile phone number PhoneNumber" field corresponding to the store management system "order number 200001", assign "bbcdef" to the "consumer identification ID_identification" field corresponding to the store management system "order number 200001", and assign "1" to the "association completion Association_completion" field corresponding to the store management system "order number 200001";

[0136] [S3.6] Perform C-round traversal loop on the store management system order database: In the store management system order database, perform steps [S3.1]-[S3.5] in sequence on the store management system order data without consumer identification, and integrate the store management system order data without consumer identification with the communication operator's signaling data, thereby identifying and filling in the "Consumer Identification ID_identification" and "Phone Number for completing payment operation" fields of the store management system order data without consumer identification, thereby achieving accurate identification of the consumer identity of the store management system order data without consumer identification.

[0137] Embodiment 3 is a method for realizing unique identification of consumer identity based on the time-space correspondence principle disclosed by the present invention, which is applicable to order data of a store management system without consumer identification, such as Figure 2 As shown:

[0138] If the image data alignment and matching result in step [S3.3] is a non-unique identity set, the corresponding avatar photo alignment and matching result of the order number 200002 data is {store avatar 2 = operator avatar 21 = operator avatar 22 = operator avatar 23 = operator avatar 28 = operator avatar 29}, it means that there are multiple merchants with personal static payment codes that have completed the payment operation at the address of 39°52'48″N 116°24'20″E and the time period of 2024 / 7 / 1011:22:01.39;

[0139] [S3.7] Extract the mobile phone number data for implementing the scanning operation: extract the picture information data {operator avatar 21, operator avatar 22, operator avatar 23, operator avatar 28, operator avatar 29} contained in the merchant's personal static payment code from the identity set {store avatar 2 = operator avatar 21 = operator avatar 22 = operator avatar 23 = operator avatar 28 = operator avatar 29}, and query the communication operator signaling database for the picture information data contained in the merchant's personal static payment code corresponding to the "implement scanning operation" The mobile phone number "set" {181****2222, 182****2222, 183****2222, 188****2222, 189****2222} is used to obtain the corresponding multiple mobile phone numbers that opened the mobile software to complete the payment operation at the address of 39°52'48″N116°24'20″E and the time period of 2024 / 7 / 1011:22:01.39; query the "order number 200002" corresponding to the merchant "store avatar 2" in the store management system order data;

[0140] [S3.8] Identify the consumer's identity through historical behavior characteristics: Use the consumer's behavior habits as the identification primary key to finely identify the set of "mobile phone numbers used to perform scanning operations" described in step [S3.7], thereby achieving unique identification of the consumer's identity.

[0141] Table 9: Step [S3.9] Details of some fields in the store management system order database

[0142] Complete the payment operation mobile phone number Consumption address Consumption times 181****2222 39°52'48"N 116°24'20"E 5 182****2222 39°52'48"N 116°24'20"E 4 183****2222 39°52'48"N 116°24'20"E 3 188****2222 39°52'48"N 116°24'20"E 2 189****2222 39°52'48"N 116°24'20"E 1

[0143] Table 10: Step [S3.9] Details of some fields in the store management system order database

[0144] Complete the payment operation mobile phone number Consumption address Consumption times 181****2222 39°52'48"N 116°24'20"E 5 182****2222 39°52'48"N 116°24'20"E 5 183****2222 39°52'48"N 116°24'20"E 5 188****2222 39°52'48"N 116°24'20"E 2 189****2222 39°52'48"N 116°24'20"E 1

[0145] [S3.8.1] Use the historical “consumption frequency” as the first matching condition to identify consumer behavior habits;

[0146] [S3.8.1.1] Extract the historical "consumption frequency" data corresponding to the mobile phone number that performs the scanning operation: use any "mobile phone number 181****2222 that performs the scanning operation" in the set of "mobile phone numbers that perform the scanning operation" {181****2222, 182****2222, 183****2222, 188****2222, 189****2222} described in step [S3.7] as the search value, and query the historical "consumption frequency Frequency_address" of "mobile phone number 181****2222 that performs the scanning operation" at "39°52'48"N116°24'20"E address" from the store management system order database.non_uniqueness_1 =5”;

[0147] [S3.8.1.2] In the order database of the store management system, perform the traversal loop operation of step [S3.8.1.1] for all elements in the set of "mobile phone numbers for scanning operations" {181****2222, 182****2222, 183****2222, 188****2222, 189****2222} described in step [S3.7], so as to obtain the historical "consumption frequency" set {Frequency_address} of all elements in the set of "mobile phone numbers for scanning operations" at the address "39°52'48"N 116°24'20"E" non_uniqueness_1 、Frequency_address non_uniqueness_2 、……、Frequency_address non_uniqueness_n3};

[0148] The historical “consumption times” set result corresponding to Table 9 is: {5, 4, 3, 2, 1};

[0149] The historical “consumption times” set result corresponding to Table 10 is: {5, 5, 3, 2, 1};

[0150] [S3.8.1.3] If there is a unique maximum value Frequency_address in the historical "consumption times" set described in step [S3.8.1.2] non_uniqueness_max =5, as shown in Table 9, the historical “Consumption Frequency” set, which means that among the multiple mobile phone numbers that opened the mobile app to complete the payment operation at the address 39°52'48″N116°24'20″E and the time period 2024 / 7 / 1011:22:05.39, Frequency_address non_uniqueness_max =5, the corresponding "scanning operation mobile phone number 181****2222" most often consumes at the store at 39°52'48″N 116°24'20″E, so it is inferred that the merchant "avatar photo store Pic_pay non_uniqueness_1 = "Order No. PurchaseOrder" corresponding to "Store Avatar 2" non_uniqueness_1 =200002" and the merchant "Avatar Photo Operator Pic_CSP" in the communication operator's signaling database non_uniqueness_address_max = Operator avatar 21" corresponds to the "Scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_address_max =181****2222” has a unique corresponding relationship;

[0151] [S3.8.1.4] Perform the scanning operation for the mobile phone number PhoneNumber_CSP as described in step [S3.8.1.3] non_uniqueness_address_max =181****2222" is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is a unique matching value, it means that PhoneNumber_CSP non_uniqueness_address_max =181****2222 has been recorded in the consumer information database, as shown in Table 8, so the consumer mobile phone number PhoneNumber_CSP non_uniqueness_address_max =181****2222" corresponds to "Consumer ID_consumer non_uniqueness_address_max =cbcdef";

[0152] [S3.8.1.5] In the store management system, assign the value cbcdef to the field "Consumer ID_identification" corresponding to the "Order Number 200002" in step [S3.8.1.3]; assign the value 181****2222 to the field "Phone Number for completing the payment operation" corresponding to the "Order Number 200002"; assign the value "1" to the field "Association_completion" corresponding to the "Order Number 200002";

[0153] Embodiment 4 is a method for realizing unique identification of consumer identity based on the time-space correspondence principle disclosed by the present invention, which is applicable to order data of a store management system without consumer identification, such as Figure 2 As shown:

[0154] Table 11: Step [S3.8.2] Details of some fields in the store management system order database

[0155]

[0156] Table 12: Step [S3.8.2] Details of some fields in the store management system order database

[0157] Complete the payment operation mobile phone number Consumer Goods Number of times Taishan cigarettes are consumed 181****2222 Taishan Cigarettes 5 182****2222 Taishan Cigarettes 4 183****2222 Taishan Cigarettes 3

[0158] Table 13: Step [S3.8.2] Details of some fields in the store management system order database

[0159] Complete the payment operation mobile phone number Consumer Goods Number of times Taishan cigarettes are consumed 181****2222 Taishan Cigarettes 5 182****2222 Taishan Cigarettes 5 183****2222 Taishan Cigarettes 3

[0160] [S3.8.2] Use the historical "consumption commodity type" as the second matching condition to identify consumer behavior habits; if there are two or more identical maximum values ​​of Frequency_address in the historical "consumption frequency" set in step [S3.8.1.3] non_uniqueness_max =5, as shown in the historical “consumption times” set in Table 10, it means that among the multiple mobile phone numbers that opened the mobile software to complete payment operations at the address 39°52'48"N116°24′20″E and the time period 2024 / 7 / 1011:22:01.39, there are multiple consumers who meet the first matching condition of frequently consuming at the store at the address 39°52'48"N116°24'20”E;

[0161] [S3.8.2.1] Extract the historical "consumer product category" data corresponding to the mobile phone number that performed the scanning operation: As shown in Table 11, in the store management system order data, query the "consumer product category Category" corresponding to the "order number 200002" mentioned in step [S3.7]. non_uniqueness_1 =Taishan Cigarettes";

[0162] [S3.8.2.2] Extract the set of mobile phone numbers that implement scanning operations corresponding to the maximum value of "Number of Consumptions": In the order database of the store management system, extract the set of mobile phone numbers that implement scanning operations corresponding to the maximum value of the historical "Number of Consumptions" described in step [S3.8.2], as shown in Table 10, recorded as {181****2222, 182****2222, 183****2222};

[0163] [S3.8.2.3] Calculate the historical consumption times corresponding to the mobile phone number that completed the payment operation corresponding to the maximum value of "consumption times": select any "scanning operation mobile phone number 181****2222" from the set of scanning operation mobile phone numbers corresponding to the maximum value of the historical "consumption times" in step [S3.8.2.2] as the search value, and query the historical consumption times of 181****2222 at the address of 39°52'48"N 116°24'20"E and purchasing Taishan cigarette products from the order database of the store management system, recorded as Frequency_category non_uniqueness_1 =5;

[0164] [S3.8.2.4] In the order database of the store management system, perform the traversal loop operation of step [S3.8.2.3] for all elements in the set of mobile phone numbers that implement the scanning operation corresponding to the maximum value of the historical "consumption frequency" in step [S3.8.2.2] in turn, so as to obtain the set of historical consumption frequency of all elements in the set of mobile phone numbers that implement the scanning operation corresponding to the maximum value of the historical "consumption frequency" in step [S3.8.2.2] at the address of 39°52'48"N 116°24'20"E and the purchase of Taishan cigarette products, recorded as {Frequency_category non_uniqueness_1 ,...,Frequency_category non_uniqueness_n4};

[0165] The corresponding set results of the historical “consumption times” of Taishan cigarettes in Table 12 are: {5, 4, 3};

[0166] The corresponding set results of the historical “consumption times” of Taishan cigarettes in Table 13 are: {5, 5, 3};

[0167] [S3.8.2.5] If there is a unique maximum value Frequency_category in the historical consumption frequency set of Taishan cigarettes purchased in step [S3.8.2.4] non_uniqueness_max =5, as shown in Table 12, it means that among the multiple mobile phone numbers that opened the mobile software to complete the payment operation at the address of 39°52'48"N 116°24'20"E and the time period of 2024 / 7 / 1011:22:01.39, Frequency_category non_uniqueness_max =5 corresponding to "Scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_category_max =181****2222" most often buys Taishan cigarettes at 39°52'48″N 116°24'20"E, so it is inferred that the merchant "headshot photo store Pic_pay non_uniqueness_1 =Store avatar 2" corresponding to "Order No. 200002" and the merchant "Avatar Photo Operator Pic_CSP" in the communication operator's signaling database non_uniqueness_category_max = Operator avatar 21" corresponds to the "Scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_category_max =181****2222” has a unique corresponding relationship;

[0168] [S3.8.2.6] Perform the scanning operation for the mobile phone number PhoneNumber_CSP as described in step [S3.8.2.5] non_uniqueness_category_max=181****2222" is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is a unique matching value, it means that PhoneNumber_CSP non_uniqueness_category_max =181****2222 has been recorded in the consumer information database, so the consumer mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_category_max =181****2222" corresponds to "Consumer ID_consumer non_uniqueness_category_max =cbcdef";

[0169] [S3.8.2.7] In the store management system, the "Consumer Identification ID_identification" field corresponding to "Order Number 200002" is assigned a value of cbcdef; the "Payment Operation Mobile Phone Number PhoneNumber" field corresponding to "Order Number 200002" is assigned a value of 181****2222; and the "Association_completion" field corresponding to "Order Number 200002" is assigned a value of "1".

[0170] Example 5 is a method for realizing unique identification of consumer identity based on the time-space correspondence principle disclosed by the present invention, which is applicable to order data of a store management system without consumer identification, such as Figure 2 As shown:

[0171] Table 14: Step [S3.8.3] Details of some fields in the store management system order database

[0172]

[0173] Table 15: Step [S3.8.3] Details of some fields in the store management system order database

[0174] Complete the payment operation mobile phone number Consumer Goods Number of consumptions during order period 181****2222 Taishan Cigarettes 5 182****2222 Taishan Cigarettes 4

[0175] [S3.8.3] Use historical "consumption time" as the third matching condition to identify consumer behavior habits; if there are two or more identical maximum values ​​of Frequency_category in the historical consumption times of purchasing Taishan cigarettes described in step [S3.8.2.4] non_uniqueness_maxAs shown in Table 13, it means that among the multiple mobile phone numbers that opened the mobile software to complete the payment operation at the address of 39°52'48"N 116°24'20″E and the time period of 2024 / 7 / 1011:22:01.39, there are two or more consumers who meet the first matching condition of "frequently consuming at the store at the address of 39°52'48"N 116°24'20″E" and the second matching condition of "frequently purchasing Taishan cigarette products";

[0176] [S3.8.3.1] Extract the historical "consumption time" data corresponding to the mobile phone number that performs the scanning operation: As shown in Table 14, in the store management system order data, query the "consumption time PayTime" corresponding to the "order number 200002" mentioned in step [S3.7]. non_uniqueness_1 =2024 / 7 / 1011:22:05.39"; Divide the 24 hours of a day into 24 time periods, and find the "PayTime non_uniqueness_1 =2024 / 7 / 1011:22:05.39" is recorded as "Order Time Split non_uniqueness_1 =11”;

[0177] [S3.8.3.2] Extract the set of mobile phone numbers that meet the first and second matching condition data and perform scanning operations: In the store management system order database, extract the set of mobile phone numbers that meet the first matching condition of "frequently consume at the store at 39°52'48"N116°24′20"E" and the second matching condition of "frequently purchase Taishan cigarettes" in step [S3.8.3], and record them as {181****2222, 182****2222};

[0178] [S3.8.3.3] Calculate the "scanning time CspTime" corresponding to the mobile phone number that performs the scanning operation corresponding to the data that meets the first and second matching conditions, which belongs to the "order time period Timesplit" in step [S3.8.3.1] non_uniqueness_1 = 11" times; from the set {181****2222, 182****2222} described in step [S3.8.3.2], select any "scanning operation mobile phone number 181****2222" as the search value, and query the "scanning time CspTime" corresponding to the address of 181****2222 at 39°52'48″N 116°24'20″E and the purchase of Taishan cigarettes from the store management system order database. non_uniqueness_time_1 " belongs to the "Order Time Period Timesplit" described in step [S3.8.3.1] non_uniqueness_1 =11" times, recorded as Frequency_time non_uniqueness_1=5;

[0179] [S3.8.3.4] In the order database of the store management system, perform the traversal loop operation of step [S3.8.3.3] for all elements in the set {181****2222, 182****2222} described in step [S3.8.3.2] in turn, so as to obtain the "scanning time CspTime" corresponding to the purchase of Taishan cigarettes at the address 39°52'48″N 116°24'20″E non_uniqueness_time " belongs to the "Order Time Period Timesplit" described in step [S3.8.3.1] non_uniqueness_1 =11" frequency set, recorded as {Frequency_time non_uniqueness_1 , ..., Frequency_time non_uniqueness_n5};

[0180] The historical “Consumption times in order time period” set result corresponding to Table 15 is: {5, 4};

[0181] [S3.8.3.5] If the number set {Frequency_time non_uniqueness_1 ,......,Frequency_time non_uniqueness_n5 There is a unique maximum value Frequency_time in} non_uniqueness_max =5, it means that among the multiple mobile phone numbers that opened the mobile app to complete payment operations at the address 39°52'48″N 116°24′20″E and the time period 2024 / 7 / 1011:22:05.39, Frequency_time non_uniqueness_max =5 corresponding to "Scanning operation mobile phone number PhoneNumber_CSP non_ u niqueness_time_max =181****2222" most often bought Taishan cigarettes at 39°52'48″N116°24'20″E and 2024 / 7 / 1011:22:01.39, so it can be inferred that the merchant "headshot photo_shop pic_pay non_uniqueness_1 = "Order No. PurchaseOrder" corresponding to "Store Avatar 2" non_uniqueness_1 =200002" and the merchant "Avatar Photo Operator Pic_CSP" in the communication operator's signaling database non_uniqueness_time_max = Operator avatar 21" corresponds to the "Scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_time_max =181****2222” has a unique corresponding relationship;

[0182] [S3.8.3.6] Perform the scanning operation for the mobile phone number PhoneNumber_CSP as described in step [S3.8.3.5] non_uniqueness_time_max =181****2222" is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is a unique matching value, it means that PhoneNumber_CSP non_uniqueness_time_max =181****2222 has been recorded in the consumer information database, so the consumer mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_time_max =181****2222" corresponds to "Consumer ID_consumer non_uniqueness_time_max =cbcdef";

[0183] [S3.8.3.7] In the store management system, assign the value cbcdef to the field "Consumer ID_identification" corresponding to "Order No. 200002"; assign the value 181****2222 to the field "Phone Number for completing the payment operation" corresponding to "Order No. 200002"; assign the value "1" to the field "Association_completion" corresponding to "Order No. 200002";

[0184] To summarize, with the historical "number of consumption times" as the first matching condition, the historical "type of goods consumed" as the second matching condition, and the historical "consumption time" as the third matching condition, through the three-layer progressive matching form, and taking the consumer behavior habits as the primary identification key, the collection of "mobile phone numbers performing scanning operations" can be precisely identified.

[0185] As shown in Table 3, the consumer information database described in [S2.3] also includes the fields of "Consumer Identification_UnionPay_consumer" and "Consumer Identification_HuaweiPay_consumer", with the mobile phone number registered for UnionPay and Huawei PAY as the associated primary key to achieve the associated identification of the same consumer's "Consumer Mobile Number Phone_consumer", "Consumer Number ID_consumer", "Consumer Identification_UnionPay_consumer" and "Consumer Identification_HuaweiPay_consumer" field data.

[0186] Figure 3 The overall flow chart of a method for realizing unique identification of consumer identity based on the principle of time-space correspondence is shown, which integrates step [S1], step [S2], and step [S3] to realize unique identification of consumer identity, including:

[0187] Through step [S1], it is determined whether there is an "Association_completion" field in the store management system order database; if not, the "Association_completion" field is created and its field value is kept NULL, and the jump process starts to recycle; if it exists, it is determined whether the "Consumer ID" in the store management system order database is NULL;

[0188] If the "consumer ID" corresponding to the order data in the store management system order database is not NULL, jump to step [S2] to find the "mobile phone number that completed the payment"; if the "mobile phone number that completed the payment" cannot be found, the jump process starts to re-circulate; if the "mobile phone number that completed the payment" is found, the consumer information database is updated and the process ends;

[0189] If the "consumer ID" corresponding to the order data in the store management system order database is NULL, jump to step [S3] to find the "mobile phone number for performing the scanning operation"; if the "mobile phone number for performing the scanning operation" cannot be found, the jump process starts to recycle; if the "mobile phone number for performing the scanning operation" is found, check whether there is a corresponding "consumer ID" in the consumer information database; if the corresponding "consumer ID" cannot be found, the jump process starts to recycle; if the corresponding "consumer ID" is found, update the consumer information database and the process ends.

[0190] Consumers consume every day and sooner or later they will pay by scanning the store management system payment code. Once a consumer has used the store management system payment code, according to the consumer identity unique identification method disclosed in Chinese patent document CN116664120A, their "consumer identification ID_identification" can be accurately determined, thereby meeting the conditions for applying step [S2] of this patent and ultimately achieving accurate consumer identity identification; for store management system order data without "consumer identification ID_identification", the consumer identity is identified through historical behavioral habit characteristics, thereby completing consumer identity inference.

[0191] 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, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for realizing unique identification of consumer identity based on the principle of time-space correspondence, wherein data is exchanged between the store management system order database and the communication operator signaling database, a unique correspondence between the "consumer identification" field in the store management system order database and the "mobile phone number for completing payment operation" field in the communication operator signaling database is established, and the unique correspondence is recorded in the consumer information database; characterized in that: include: [S1] Initialization of the store management system order database data: Check whether the "Association_completion" field exists in the store management system order database; if it does not exist, create the "Association_completion" field and keep its field value as NULL, and jump to the process to start a new cycle; if it exists, determine whether the "Consumer ID" in the store management system order database is NULL; [S2] Integration of store management system order data with consumer identification and communication operator signaling data: If the "consumer identification" corresponding to the order data in the store management system order database is not NULL, the store management system order data with consumer identification and the communication operator signaling data are screened and aligned in the time dimension and space dimension, including: [S2.1] Extraction of order data from the store management system with consumer identification: Extract n1 "Order Number PurchaseOrder" field, "PayTime" field, and "Consumption_address" field data corresponding to any "Consumer Identification ID_identification" field data whose "Related Field" is NULL and "Consumer Identification" field is not NULL, expressed as {(ID_identification label_1 、PurchaseOrder label_1 、PayTime label_1 、Consumption_address label_1 ), (ID_identification label_1 、PurchaseOrder label_2 、PayTime label_2 、Consumption_address label_2 ),...,(ID_identification label_1 、PurchaseOrder label_n1 、PayTime label_n1 、Consumption_address label_n1 )}; the measurement unit of the "PayTime" is "milliseconds", and the "Consumption_address" is a combination of a set of longitude and latitude numbers; [S2.2] Perform multiple rounds of spatiotemporal data integration and alignment on the store management system order data with consumer identification: Use the "Consumption_address" field and "Consumption time PayTime" field data of the store management system order data obtained in step [S2.1] as the search primary key, and align and match them with the "Base station coverage range Csp_address" field and "Scan code time CspTime" field data in the communication operator signaling database one by one, and search for the set of mobile phone numbers whose "Consumption address Consumption_address" is within the "Base station coverage range Csp_address" and whose "Consumption time PayTime" and "Scan code time CspTime" are in the same time period, that is, the set of all mobile phone numbers that have opened the mobile payment software in the Consumption_address address and PayTime time period, recorded as {PhoneNumber_CSP label }; In the first round of search, using formula 2.2.1 as the search condition, the search result {PhoneNumber_CSP label_1 }; (Consumption_address label_1 ∈Csp_address label_1 )∩[(PayTime label_1 -T_Delay_label)≤CspTime label_1 <PayTime labei_1 Formula 2.2.1; In the second round of search, using formula 2.2.2 as the search condition, the search result {PhoneNumber_CSP label_2 }; (Consumption_address label_2 ∈Csp_address label_2 )∩[(PayTimel label_2 -T_Delay_label)≤CspTime label_2 <PayTime label_2 Formula 2.2.2; …… In the n2th round of search, the search result {PhoneNumber_CSP label_n2 }; (Consumption_address label_n2 ∈Csp_address label_n2 )∩[(PayTime label_n2 -T_Delay_label)≤CspTime label_n2 <PayTime label_n2 Formula 2.2.n2; Among them, T_Delay_label≤300000, n2≥1, n1≥n2; [S2.3] Intersection of multiple rounds of search results: Intersection of the n2 sets of mobile phone numbers obtained in step [S2.2] is taken, as shown in formula 2.3.1, until the result of the operation is a single data set; PhoneNumber_CSP label_end ={PhoneNumber_CSP label_1} ∩ {PhoneNumber_CSP label_2} ∩...... ∩ {PhoneNumber_CSP label_n2}; Formula 2.3.1 Through the above steps, establish "Consumer ID_identification label_1 " and " implement scanning operation mobile phone number PhoneNumber_CSP label_end "Unique correspondence; the "consumer identification ID_identification label_1 " is recorded in the "consumer number ID_consumer" field of the consumer information database, and the "scanning operation mobile phone number PhoneNumber_CSP label_end " is recorded in the "consumer mobile phone number Phone_consumer" field of the consumer information database; [S2.4] Round A of traversal loop for the store management system order database: In the store management system order database, use formula 2.4.1 as the search primary key and assign PhoneNumber_CSP to the search result column "Complete payment operation mobile phone number PhoneNumber" label_end , set the value of "1" to the "Association_completion" field; (Consumer ID = ID_identification label_1 )∩(association completed=NULL) Formula 2.4.1 [S2.5] Perform round B of traversal loop on the store management system order database: In the store management system order database, perform steps [S2.1] to [S2.4] on the store management system order data with consumer identification in turn, so as to achieve accurate correspondence between the "Mobile phone number PhoneNumber_CSP used for scanning operation" field in the communication operator signaling database and the "Consumer identification ID_identification" field in the store management system order database.

2. According to claim 1, a method for realizing unique identification of consumer identity based on the principle of time-space correspondence, characterized in that: [S2.2] The T_Delay_label=120000.

3. The method for realizing unique identification of consumer identity based on the time-space correspondence principle according to claim 1, characterized in that: [S2.2] n2=6.

4. A method for uniquely identifying a consumer based on the time-space correspondence principle according to any one of claims 1 to 3, characterized in that: Including [S3] integration of store management system order data without consumer identification and communication operator signaling data, that is, using the image information contained in the personal static payment code posted by the merchant store as the identification primary key, the store management system order data without consumer identification and the communication operator signaling data are screened and aligned in a single round in the time dimension and space dimension: [S3.1] Extraction of order data from the store management system without consumer identification: Extract the merchant's "Avatar Photo_Store Pic_pay" field and the corresponding "Order Number PurchaseOrder" field, "Consumption Time PayTime" field, and "Consumption Address Consumption_address" field data from any store management system order data where the consumer completes payment using the personal static payment code posted by the store and the "Consumer Identification" field is NULL, expressed as (Pic_pay unlabel_1 、PurchaseOrder unlabel_1 、PayTime unlabel_1 、Consumption_address unlabel_1 ); the measurement unit of the "PayTime" is "milliseconds", and the "Consumption_address" is a combination of a set of longitude and latitude numbers; [S3.2] Perform a single-round spatiotemporal data alignment on the store management system order data without consumer identification: Use the "Consumption_address" field and "Consumption time PayTime" field data of the store management system order data obtained in step [S3.1] as the search primary key, and align and match them with the "Base station coverage range Csp_address" field and "Scanning code time CspTime" field data in the communication operator's signaling database one by one, and search for the set of mobile phone numbers whose "Consumption address Consumption_address" is within the "Base station coverage range Csp_address" and whose "Consumption time PayTime" and "Scanning code time CspTime" are in the same time period. That is, use Formula 3.2.1 as the search condition, and the search result is the "Mobile phone number PhoneNumber_CSP that performs the scanning operation" set, recorded as {PhoneNumber_CSP unlabel }; (Consumption_address unlabel ∈Csp_address unlabel )∩[(PayTime unlabel _T_Delay_unlabel)≤CspTime unlabel ≤(PayTime unlabel +T_Delay_unlabel)] Formula 3.2.1; Among them, T_Delay_unlabel≤300000; [S3.3] Align the avatar data of the store management system order data without consumer identification: use the "avatar photo_store Pic_pay" field data in step [S3.1] as the identification primary key, and the "scanning operation mobile phone number" set {PhoneNumber_CSP unlabel }Record the merchant's "Avatar Photo_Operator Pic_CSP" field data in the corresponding communication operator's signaling database to perform image data alignment and matching; [S3.4] Determination of the result of the portrait data integration alignment: If the picture data alignment matching result in step [S3.3] is a single identity {Pic_pay only1 =Pic_CSP only1 }, that is, find the consumption_address only1 Address, PayTime only1 The unique merchant personal static payment code that completes the payment in the time period, and can find the corresponding Csp_address only1 Address, CspTime only1 The unique mobile phone number that has opened the mobile app to complete the payment operation during the time period, and then determine the merchant's "Avatar Photo_Shop Pic_pay only1 "Corresponding to" order number PurchaseOrder only1 "With merchants in the communication operator's signaling database" avatar photo_store pic_CSP only1 "Corresponding to" implement scanning operation mobile phone number PhoneNumber_CSP only1 "There is a unique correspondence; [S3.5] Update the order data of the store management system without the consumer identification: perform the scanning operation of the mobile phone number PhoneNumber_CSP as described in step [S3.4] only1 " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP only1 =Phone_consumer only1 , then PhoneNumber_CSP only1 It has been recorded in the consumer information database, so the consumer's mobile phone number can be obtained. only1 "Corresponding to" consumer number ID_consumer only1 "; store management system "order number PurchaseOrder only1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value "PhoneNumber_CSP only1 ", the store management system "order number PurchaseOrder only1 "The corresponding "Consumer Identification ID_identification" field is assigned the value "ID_consumer only1 ", the store management system "order number PurchaseOrder only1 "The corresponding "Association_completion" field is assigned a value of "1"; [S3.6] Traverse the store management system order database C round loop: In the store management system order database, execute steps [S3.1]-[S3.5] traverse loop operations on the store management system order data without consumer identification in turn, and integrate the store management system order data without consumer identification with the communication operator's signaling data, so as to identify and fill in the "Consumer identification ID_identification" and "Complete payment operation mobile phone number PhoneNumber" fields of the store management system order data without consumer identification, so as to realize accurate identification of the consumer identity of the store management system order data without consumer identification.

5. The method for realizing unique identification of consumer identity based on the time-space correspondence principle according to claim 4, characterized in that: [S3.1] The personal static payment codes posted by the store include: WeChat, Alipay, UnionPay, Huawei PAY and other personal static payment codes provided by other mobile payment service providers.

6. The method for realizing unique identification of consumer identity based on the time-space correspondence principle according to claim 4, characterized in that: [S3.2] The T_Delay_unlabel=120000.

7. The method for realizing unique identification of consumer identity based on the time-space correspondence principle according to claim 4, characterized in that: If the picture data alignment matching result in step [S3.3] is a non-unique identity set, it is recorded as {Pic_pay non_uniqueness_1 =Pic_CSP non_uniqueness_1 =Pic_CSP non_uniqueness_2 =......=Pic_CSP non_uniqueness_n3 }, which means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 There are multiple merchants with personal static payment codes in the time period to complete the payment operation; [S3.7] Extract the mobile phone number data for the scanning operation: Extract the identity set {Pic_pay non_uniqueness_1 =Pic_CSP non_uniqueness_1 =Pic_CSP non_uniqueness_2 =......=Pic_CSP non_uniqueness_n3 } The picture information data contained in the merchant's personal static payment code {Pic_CSP non_uniqueness_1 、Pic_CSP non_uniqueness_2 , ..., Pic_CSP non_uniqueness_n3 }, query the communication operator's signaling database for the "scanning mobile phone number" set corresponding to the image information data contained in the merchant's personal static payment code {PhoneNumber_CSP non_uniqueness_1 、PhoneNumber_CSP non_uniqueness_2 , ..., PhoneNumber_CSP non_uniqueness_n3 }, so as to get the corresponding consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Multiple mobile phone numbers that have opened the mobile app to complete payment operations during a certain period of time; query the merchant's "Avatar Photo_Shop Pic_pay" in the order data of the store management system non_uniqueness_1 "Corresponding to" order number PurchaseOrder non_uniqueness_1 ”; [S3.8] Identify the consumer's identity through historical behavior characteristics: Use the consumer's behavior habits as the identification primary key to finely identify the set of "mobile phone numbers used to perform scanning operations" described in step [S3.7], thereby achieving unique identification of the consumer's identity.

8. According to the method for uniquely identifying a consumer based on the time-space correspondence principle of claim 7, the step [S3.8] of identifying the consumer through historical behavior characteristics is characterized by: [S3.8.1] Use the historical "consumption frequency" as the first matching condition to identify consumer behavior habits; [S3.8.1.1] Extract the historical "consumption times" data corresponding to the mobile phone number that performs the scanning operation: Take the "scanning operation mobile phone number" set {PhoneNumber_CSP non_uniquenessn_1 、PhoneNumber_CSP non_uniqueness_2 ,......,PhoneNumber_CSP non_uniqueness_n3 } any one of "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_1 " is the search value, query " from the store management system order database to implement the scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_1 "Consumption_address non_uniqueness_1 Address" historical" consumption frequency Frequency_address non_uniqueness_1 ”; [S3.8.1.2] In the store management system order database, the set of "scanning operation mobile phone numbers" {PhoneNumber_CSP non_uniqueness_1 、PhoneNumber_CSP non_uniqueness_2 ,......,PhoneNumber_CSP non_uniqueness_n3 } executes step [S3.8.1.1] to traverse the loop operation, thereby obtaining all elements in the "scan operation mobile phone number" set in "Consumption_address non_uniqueness_1 Address" historical "consumption times" collection {Frequency_address non_uniqueness_1 、Frequency_address non_uniqueness_2 、……、Frequency_address non_uniqueness_n3 }; [S3.8.1.3] If there is a unique maximum value Frequency_address in the historical "consumption times" set described in step [S3.8.1.2] non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Frequency_address non_uniqueness_max Corresponding "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_address_max "Most often in Consumption_address non_uniqueness_1 The address of the store consumption, so it is inferred that the merchant's "Avatar Photo_Store Pic_pay non_uniqueness_1 "Corresponding to" order number PurchaseOrder non_uniqueness_1 "With merchants in the communication operator's signaling database" avatar photo_operator Pic_CSP non_uniqueness_address_max "Corresponding to" implement scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_address_max "There is a unique correspondence; [S3.8.1.4] Perform the scanning operation of the mobile phone number PhoneNumber_CSP as described in step [S3.8.1.3] non_uniqueness_address_max " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP non_uniqueness_address_max =Phone_consumer non_uniqueness_address_max , then PhoneNumber_CSP non_uniqueness_address_max It has been recorded in the consumer information database, so the consumer's mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_address_max "Corresponding to" consumer number ID_consumer non_uniqueness_address_max ”; [S3.8.1.5] In the store management system, enter the "PurchaseOrder" non_uniqueness_1 "The corresponding "Consumer Identification ID_identification" field is assigned the value ID_consumer non_uniqueness_address_max ; Change the "order number PurchaseOrder non_uniqueness_1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value PhoneNumber_CSP non_uniqueness_address_max ; Change the "order number PurchaseOrder non_uniqueness_max "The corresponding "Association_completion" field is assigned a value of "1"; [S3.8.2] Use the historical "consumption commodity type" as the second matching condition to identify consumer behavior habits; if there are two or more identical maximum values ​​Frequency_address in the historical "consumption frequency" set in step [S3.8.1.3] non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Among the multiple mobile phone numbers that have opened the mobile app to complete payment operations during the period, there are two or more consumers who often meet the consumption_address non_uniqueness_1 The first matching condition for address store consumption; [S3.8.2.1] Extract the historical "consumed goods category" data corresponding to the mobile phone number that performed the scanning operation: In the store management system order data, query the "order number PurchaseOrder" mentioned in step [S3.7] non_uniqueness_1 "Corresponding" consumer goods category non_uniqueness_1 ”; [S3.8.2.2] Extract the set of mobile phone numbers that implement scanning operations corresponding to the maximum value of "Consumption Times": In the store management system order database, extract the set of mobile phone numbers that implement scanning operations corresponding to the maximum value of the historical "Consumption Times" described in step [S3.8.2], recorded as {PhoneNumber_CSP non_uniqueness_address_1 , ..., PhoneNumber_CSP non_uniqueness_address_n4 }; [S3.8.2.3] Calculate the historical consumption times corresponding to the mobile phone number that completed the payment operation corresponding to the maximum value of "consumption times": any "scanning operation mobile phone number PhoneNumber_CSP" in the set of mobile phone numbers that performed the scanning operation corresponding to the maximum value of the historical "consumption times" in step [S3.8.2.2] non_uniqueness_address_1 " is the search value, and PhoneNumber_CSP is queried from the store management system order database non_uniqueness_address_1 Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1 The historical consumption frequency of the product, recorded as Frequency_category non_uniqueness_1 ; [S3.8.2.4] In the store management system order database, perform the traversal loop operation of step [S3.8.2.3] for all elements in the set of mobile phone numbers for scanning operations corresponding to the maximum value of the historical "consumption times" in step [S3.8.2.2], so as to obtain all elements in the set of mobile phone numbers for scanning operations corresponding to the maximum value of the historical "consumption times" in step [S3.8.2.2] in Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1 The historical consumption frequency of a product is recorded as {Frequency_category non_uniqueness_1 ,...,Frequency_category non_uniqueness_n4 }; [S3.8.2.5] If step [S3.8.2.4] purchases Category non_uniqueness_1 There is a unique maximum value Frequency_category in the historical consumption frequency set of the product non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Frequency_category non_uniqueness_max Corresponding "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_category_max "Most often in Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1 Therefore, it is inferred that the merchant's "avatar photo_shop pic_pay non_uniqueness_1 "Corresponding to" order number PurchaseOrder non_uniqueness_1 "With merchants in the communication operator's signaling database" avatar photo_operator Pic_CSP non_unlqueness_category_max "Corresponding to" implement scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_category_max "There is a unique correspondence; [S3.8.2.6] Perform the scanning operation of the mobile phone number PhoneNumber_CSP as described in step [S3.8.2.5] non_uniqueness_category_max " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP non_uniqueness_category_max =Phone_consumer non_uniqueness_category_max , then PhoneNumber_CSP non_uniqueness_category_max It has been recorded in the consumer information database, so the consumer's mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_category_max "Corresponding to" consumer number ID_consumer non_uniqueness_category_max ”; [S3.8.2.7] In the store management system, set the "Order Number PurchaseOrder non_uniqueness_1 "The corresponding "Consumer Identification ID_identification" field is assigned the value ID_consumer non_uniqueness_category_max ; Change the "order number PurchaseOrder non_uniqueness_1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value PhoneNumber_CSP non_uniqueness_category_max ; Change the "order number PurchaseOrder non_uniqueness_1 "The corresponding "Association_completion" field is assigned a value of "1"; [S3.8.3] Use historical "consumption time" as the third matching condition to identify consumer behavior habits; if the purchase category in step [S3.8.2.4] non_uniqueness_1 There are two or more identical maximum values ​​of Frequency_category in the historical consumption frequency set of the product non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Among the multiple mobile phone numbers that have opened the mobile app to complete payment operations during the period, two or more consumers meet the "frequent consumption_address non_uniqueness_1 The first matching condition of address store consumption" and "frequently purchased Category non_uniqueness_1 The second matching condition of the product"; [S3.8.3.1] Extract the historical "consumption time" data corresponding to the mobile phone number that performed the scanning operation: In the store management system order data, query the "order number PurchaseOrder" mentioned in step [S3.7] non_uniqueness_1 "The corresponding "PayTime non_uniqueness_1 "; Divide the 24 hours of a day into m time periods, and find the "PayTime" non_uniqueness_1 "The corresponding time period is recorded as "Order Time Period Timesplit non_uniqueness_1 ”; [S3.8.3.2] Extract the set of mobile phone numbers that implement the scanning operation corresponding to the data that meets the first and second matching conditions: In the store management system order database, extract the mobile phone numbers that meet the "frequent consumption_address" requirement in step [S3.8.3] non_uniqueness_1 The first matching condition for address store consumption is "Frequently purchased Category" non_uniqueness_1 The set of mobile phone numbers for scanning operations corresponding to the second matching condition of the product is recorded as {PhoneNumber_CSP non_uniqueness_time_1 ,......,PhoneNumber_CSP non_uniqueness_time_n5 }; [S3.8.3.3] Calculate the "scanning time CspTime" corresponding to the mobile phone number that performs the scanning operation corresponding to the data that meets the first and second matching conditions, which belongs to the "order time period Timesplit" described in step [S3.8.3.1] non_uniqueness_1 " times; from step [S3.8.3.2] {PhoneNumber_CSP non_uniqueness_time_1 ,......,PhoneNumber_CSP non_uniqueness_time_n5 } collection, select any one "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_time_1 " is the search value, and PhoneNumber_CSP is queried from the store management system order database non_uniqueness_time_1 Consumption_address non_uniqueness_1 Address, Purchase Category non_uniqueness_1 The "scanning time CspTime" corresponding to the product non_uniqueness_time_1 "Belongs to the "Order Time Period Timesplit" described in step [S3.8.3.1] non_uniqueness_1 "Time, recorded as Frequency_time non_uniqueness_1 ; [S3.8.3.4] In the store management system order database, the {PhoneNumber_CSP non_uniqueness_time_1 ,......,PhoneNumber_CSP non_uniqueness_time_n5 }Execute step [S3.8.3.3] to loop through all elements in the collection, and obtain the non_uniqueness_1 Address, Purchase Category non_uniqueness_1 The "scanning time CspTime" corresponding to the product non_uniqueness_time "Belongs to the "Order Time Period Timesplit" described in step [S3.8.3.1] non_uniqueness_1 "Frequency_time non_uniqueness_1 ,......,Frequency_time non_uniqueness_n5 }; [S3.8.3.5] If the number set {Frequency_time non_uniqueness_1 ,......,Frequency_time non_uniqueness_n5 There is a unique maximum value Frequency_time in} non_uniqueness_max , it means that in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Frequency_time non_uniqueness_max Corresponding "Scan operation mobile phone number PhoneNumber_CSP non_uniqueness_time_max "Most often in Consumption_address non_uniqueness_1 Address, PayTime non_uniqueness_1 Time to buy Category non_uniqueness_1 Therefore, it is inferred that the merchant's "avatar photo_shop pic_pay non_uniqueness_1 "Corresponding to" order number PurchaseOrder non _ uniqueness_1 "With merchants in the communication operator's signaling database" avatar photo_operator Pic_CSP non_uniquenesstime_max "Corresponding to" implement scanning operation mobile phone number PhoneNumber_CSP non_uniqueness_time_max "There is a unique correspondence; [S3.8.3.6] Perform the scanning operation of the mobile phone number PhoneNumber_CSP as described in step [S3.8.3.5] non_uniqueness_time_max " is the search value, and the search is performed in the "consumer mobile phone number Phone_consumer" field data in the consumer information database in step [S2.3]; if the search result is the only matching value PhoneNumber_CSP non_uniqueness_time_max =Phone_consumer non_uniqueness_time_max , then PhoneNumber_CSP non_uniqueness_time_max It has been recorded in the consumer information database, so the consumer's mobile phone number PhoneNumber_CSP can be obtained. non_uniqueness_time_max "Corresponding to" consumer number ID_consumer non_uniqueness_time_max ”; [S3.8.3.7] In the store management system, set the "Order Number PurchaseOrder non_uniqueness_1 "The corresponding "Consumer Identification ID_identification" field is assigned the value ID_consumer non_uniqueness_time_max ; Change the "order number PurchaseOrder non_uniqueness_1 "The corresponding "Complete payment operation mobile phone number PhoneNumber" field is assigned the value PhoneNumber_CSP non_uniqueness_time_max ; Change the "order number PurchaseOrder non_uniqueness_1 "The corresponding "Association_completion" field is assigned a value of "1"; With the historical "number of consumption times" as the first matching condition, the historical "type of goods consumed" as the second matching condition, and the historical "consumption time" as the third matching condition, through the three-layer progressive matching form, the consumer behavior habits are used as the primary identification key to realize the fine identification of the "mobile phone number that performs scanning operations" collection.

9. A method for realizing unique identification of consumer identity based on the principle of time-space correspondence according to claim 8, characterized in that: [S3.8.3.1] m=24.

10. The method for realizing unique identification of consumer identity based on the time-space correspondence principle according to claim 8, characterized in that: [S2.3] The consumer information database also includes the fields "Consumer ID_UnionPay_consumer" and "Consumer ID_HuaweiPay_consumer", with the mobile phone number registered for UnionPay and Huawei PAY as the associated primary key to achieve the associated identification of the same consumer's "Consumer Mobile Number Phone_consumer" "Consumer Number ID_consumer" "Consumer ID_UnionPay_consumer" and "Consumer ID_HuaweiPay_consumer" field data.

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