A method and system for processing geographic locations

Abstract

The present specification discloses a geographic position processing method and system, the method starts from the perspective of merchant group information sharing, excavates the transaction association between merchant groups, determines a merchant cluster with transaction association from the merchant groups, and determines a first type of merchant from the merchant cluster; the first type of merchant is a merchant with known transaction geographic position in the merchant cluster, so as to determine the transaction position of the merchant with unknown transaction geographic position in the merchant cluster.

Description

Technical Field

[0001] This specification relates to the field of payments, and in particular to a method and system for processing geographic location. Background Technology

[0002] With the development of the Internet, more and more merchants support online transactions. In order to facilitate the management of merchants, different risk control strategies are usually adopted according to the location of the merchant, or the future business direction is determined according to the location of the merchant.

[0003] All of the above scenarios require knowledge of the merchant's location; therefore, a more reliable solution is needed to improve the accuracy of the merchant's location. Summary of the Invention

[0004] Firstly, embodiments of this specification provide a method for processing geographic location, the method comprising:

[0005] Identify merchant clusters with transaction relationships from the merchant groups;

[0006] A first category of merchants is determined from the merchant cluster; the first category of merchants are those whose transaction geographical locations are known within the merchant cluster.

[0007] Based on the transaction geographical location of the first type of merchants in the merchant cluster, the transaction geographical location of the second type of merchants in the merchant cluster is determined; the second type of merchants are those whose transaction geographical location is unknown in the merchant cluster.

[0008] Secondly, embodiments of this specification provide a geographic location processing system, including:

[0009] The first determining unit is used to identify merchant clusters with transaction relationships from the merchant group;

[0010] The second determining unit is used to determine a first type of merchant from the merchant cluster; the first type of merchant is a merchant in the merchant cluster whose transaction geographical location is known.

[0011] The third determining unit is used to determine the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster; wherein the second type of merchants are merchants whose transaction geographical location is unknown in the merchant cluster.

[0012] Thirdly, embodiments of this specification provide a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the above-described method.

[0013] Fourthly, embodiments of this specification provide a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described method.

[0014] The above-described one or more technical solutions in the embodiments of this specification have at least the following technical effects:

[0015] This specification describes a method and system for processing geographical location. The method, from the perspective of information sharing among merchant groups, mines transaction relationships between merchant groups, identifies merchant clusters with transaction relationships within these groups, and then identifies a first type of merchant from these clusters. This first type of merchant consists of merchants within the merchant clusters whose transaction geographical locations are known. The method aims to determine the transaction locations of merchants within the merchant clusters whose transaction geographical locations are unknown, thereby achieving the purpose of transmitting and disseminating transaction geographical locations among merchants and improving the accuracy of merchant transaction geographical locations. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this specification, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the geographic location processing method provided in the embodiments of this specification;

[0018] Figure 2 A schematic diagram of a geographic location processing system provided in the embodiments of this specification;

[0019] Figure 3 This is a schematic diagram of an electronic device provided as an embodiment of this specification. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments in this specification clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0021] This specification discloses one or more embodiments of a method and system for processing geographical location. Since the geographical location of merchants is relatively fixed, and there are strong transactional relationships between merchants within the same business district, accurate collection of transaction geographical locations is crucial for managing cross-border transactions and preventing risks such as marketing fraud. Transaction geographical location typically refers to a geographical location including latitude and longitude information. This embodiment, from the perspective of information sharing among merchant groups, mines transactional relationships between merchant groups to determine the transaction location of merchants with unknown transaction geographical locations, achieving the purpose of transmitting and disseminating transaction geographical locations among merchants and improving the accuracy of merchant transaction geographical locations.

[0022] The geographical location of a merchant's transaction serves as the foundation for various scenarios such as risk control, management, decision-making, and business development for the merchant. If the geographical location of a merchant's transaction is accurately defined, the accuracy of subsequent business operations based on the merchant can be greatly improved, and system resources can be significantly saved.

[0023] Taking management decisions as an example, merchants in different geographical locations will be managed using different management models or with different decisions. Investing in management resources (such as resources invested in management system development) can yield higher reach and management returns in the geographical location of the transaction. However, if the geographical location of the transaction is not accurately defined, even with the same amount of management resources invested, it will be difficult to achieve the same level of reach and management returns, leading to wasted computer resources or incorrect risk data identification, among other consequences. This embodiment employs the aforementioned technical solution to improve the accuracy of geographical location segmentation, thereby enabling precise investment of management resources, avoiding waste, and achieving high reach and management returns in the geographical location of the transaction.

[0024] Taking risk control as an example, if a merchant's transaction location is not accurately defined (e.g., a merchant is identified as being in area B instead of area A), it is difficult to accurately pinpoint the merchant's transaction location. Even with the same amount of risk control resources invested (e.g., risk control decision-making, risk prediction resources, etc.), the accuracy of risk control will be poor. For example, if a merchant should be located in area A, but various strategies and models designed for area B are used for risk control and prediction, this will result in a significant waste of risk control resources. However, if the transaction location is accurately defined, then a series of risk control strategies based on this can accurately control and predict risks, thereby greatly saving risk control resources, avoiding waste, and achieving better risk control results.

[0025] See Figure 1 The method includes the following steps:

[0026] Step 100: Identify merchant clusters with transaction associations from the merchant groups.

[0027] In this embodiment, merchant groups are divided according to the following method: Merchants are divided based on their registered location to obtain the merchant groups. Specifically, merchants can be included in groups based on their registered location filled in during merchant access, to avoid situations where all merchant transaction locations are empty. Alternatively, merchants can be divided based on their transaction addresses within a preset geographical region to obtain the merchant groups. Specifically, the transaction location obtained by the merchant during a transaction can be used to group merchants according to a preset geographical region. The size of the merchant groups is determined based on the actual situation. For example, a preset geographical region, "county," can be used as the unit for dividing merchant groups. If a merchant has transactions occurring in that county within a certain time interval, they are included in the merchant group for that county.

[0028] The merchant group comprises two groups: those with known transaction locations and those with unknown transaction locations. Merchants with unknown transaction locations do not lack any transaction location information; rather, they possess some information, but it is insufficient to determine their exact location. For example, a merchant with a low-precision transaction location might be located in a certain county, but their exact location is unknown. Or, a merchant might have both their registered address and actual business operations within the same county, but in different locations.

[0029] Merchant clusters exhibit related transactions, meaning that merchants within a cluster share interconnected attributes during transactions with users. Specifically, merchant clusters can be identified from merchant groups based on these interconnected attributes. These attributes include identical transaction partners, transactions using accounts on the same device, or accounts corresponding to the same MAC address. If two merchants transact with the same user, use accounts on the same device, or use accounts corresponding to the same MAC address, they can be grouped into the same merchant cluster. Therefore, merchants within a cluster are interconnected, allowing for the discovery of transaction relationships between merchant groups. This enables the identification of transaction locations for merchants with unknown geographical locations, facilitating the propagation of transaction geolocation among merchants and improving the accuracy of merchant transaction geolocation.

[0030] In the specific implementation process, merchant clusters with transaction relationships within a preset time interval can be identified from the merchant group to avoid reducing the correlation between merchants within the cluster due to excessive time. The preset time interval can be set arbitrarily, for example, identifying merchant clusters with transaction relationships within 1 day or 5 days.

[0031] In practice, different implementation methods will be used depending on the nature of the related-party transaction.

[0032] As an optional embodiment, a set of merchants with transaction data is determined from the merchant group. Specifically, a set of merchants with transaction data within a preset time interval is determined from the merchant group. For example, all merchants in a county that generated transaction data within one day are identified as the set of merchants. Within this set of merchants, if two merchants have most of the same users, it indicates that the two merchants are located close to each other, such as a clothing store and a milk tea shop next to each other. Therefore, "user overlap" can be used to characterize the correlation between merchants in the set of merchants, and a merchant cluster with related transactions can be obtained accordingly. Thus, the transaction addresses of each merchant in the merchant cluster are close. The user overlap of each merchant refers to the degree to which each merchant and every other remaining merchant in the set of merchants have the same users. Therefore, the user overlap of each merchant in the set of merchants can be obtained; the merchant cluster is determined based on the user overlap of all merchants in the set of merchants.

[0033] Furthermore, for each merchant in the set of trading merchants, the first number of users sharing the same trading users with that merchant and each of the remaining trading merchants is obtained, as well as the second number of users combining the number of users of that merchant and each of the remaining trading merchants; the second number of users refers to the sum of the number of users of that merchant and the number of users of any remaining trading merchants. Based on the first number of users and the second number of users, the user overlap rate between that merchant and each of the remaining trading merchants is obtained.

[0034] Specifically, the user overlap between merchants and other merchants is calculated using the following formula:

[0035] User overlap = N_(A∩B) / N_(A∪B)

[0036] Here, A represents a specific merchant in the set of trading merchants, B represents a remaining merchant besides A, N_(A∩B) represents the users who transact together with merchants A and B (intersection), and the denominator of N_(A∪B) is the total number of users corresponding to merchants A and B (union). Higher user overlap indicates stronger information consistency between the two merchants and closer geographical proximity in their transactions. For example, a coffee shop and a bakery located in the same shopping mall.

[0037] Based on the above formula, the user overlap of all merchants in the transaction merchant set can be calculated, and the merchant cluster can be determined accordingly.

[0038] As an optional embodiment, in the process of determining merchant clusters with transaction associations from a merchant group, several merchants who have used accounts corresponding to the same device are identified as the merchant cluster; or several merchants who have used accounts corresponding to the same MAC address are identified as the merchant cluster. Further, a preset time interval can also be used as a condition for determining merchant clusters. For example, several merchants who have used accounts corresponding to the same device within a preset time interval are identified as the merchant cluster. Specifically, the merchant group is clustered based on device, for example, merchants who have used accounts corresponding to the same device within one day are grouped into one cluster. Such merchant clusters are often found among indirectly connected merchants, such as those managed by the same small acquiring institution, or merchants belonging to the same household. Additionally, the merchant group can be clustered based on Wi-Fi MAC address; merchants who have used accounts corresponding to the same Wi-Fi MAC address within one day are grouped into one cluster. Such merchant groups are often found among merchants located in the same business district, or merchants who have logged into the same account using public Wi-Fi.

[0039] Step 102: Identify the first type of merchant from the merchant cluster.

[0040] The first category of merchants refers to those whose transaction geographical location is known within the merchant cluster. Specifically, the merchant cluster includes merchants with known transaction geographical locations and merchants with unknown transaction geographical locations. During the transaction process, if the accuracy of the transaction geographical location is insufficient, or if the merchant has not authorized the system to collect the transaction geographical location, then the transaction geographical location is unknown.

[0041] In determining the first category of merchants, if the merchant cluster is determined based on user overlap, then among merchants with known transaction geographical locations, an overlap threshold can be further set, and merchants with user overlap exceeding the overlap threshold can be selected as the first category of merchants. Alternatively, merchants can be sorted by user overlap, and the merchants at the top of the sorted list (within a preset number of positions) can be selected as the first category of merchants.

[0042] Merchant clusters are defined by accounts associated with the same device or the same MAC address. Therefore, within a merchant cluster, the transaction distance between merchants exceeding a preset data threshold may be higher or lower than the preset distance threshold. For example, if merchants with preset data have a transaction distance of less than 1 kilometer between each other, the merchants in the cluster are mostly clustered together. Conversely, if merchants with preset data have a distance greater than 1 kilometer between each other, the merchants in the cluster are mostly dispersed.

[0043] Specifically, within a merchant cluster, merchants with preset data and transaction distances higher than a preset distance threshold are identified as Class I merchants; or within a merchant cluster, merchants with preset data and transaction distances lower than a preset distance threshold are identified as Class I merchants.

[0044] Step 104: Determine the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster.

[0045] The second type of merchant refers to merchants whose geographical location is unknown within the merchant cluster.

[0046] In determining the transaction geographical locations of the second type of merchants within a merchant cluster, since the transaction geographical locations of all merchants in the first type of merchant cluster are known, the average location of the transaction geographical locations of the first type of merchants can be determined and used as the transaction geographical locations of the second type of merchants. For example, if there are 5 first-type merchants in the merchant cluster and their latitude and longitude are known, the average latitude and longitude can be obtained based on these 5 locations and used as the transaction geographical locations of the second type of merchants.

[0047] As an alternative implementation, although merchants are in the same cluster, the clustering of the first type of merchants is unknown. If the first type of merchants are relatively dispersed, using the average value to determine the transaction geographical location of the second type of merchants may affect the accuracy. Considering this issue, the merchant cluster can be pre-processed using preset distance thresholds and merchant distance values ​​to obtain different scenarios. Further processing can then be applied based on these scenarios to improve the accuracy of the merchant transaction geographical location. For example, if the transaction distance of all merchants in the first type of merchant cluster is higher than the preset distance threshold, then most merchants in the cluster are clustered together, and the average value method can be used. If most merchants in the cluster are dispersed, other methods can be used.

[0048] Specifically, the following steps can be performed: Based on the transaction geographical locations of all merchants in the first category of merchants, determine the merchant distance value of all merchants belonging to the first category of merchants. The merchant distance value is used to represent the relative distance between any two merchants in the first category of merchants.

[0049] If the distance values ​​of merchants in the first category exceeding the preset data meet the distance requirement, that is, if the distance values ​​of merchants in the first category exceeding the preset data are higher than the preset distance threshold, the average transaction geographical location of the first category of merchants is determined as the transaction geographical location of the second category of merchants in the merchant cluster. Furthermore, the transaction geographical locations of merchants corresponding to distances higher than the preset distance threshold can be obtained, and the average transaction geographical location of these merchants is determined as the transaction geographical location of the second category of merchants in the merchant cluster, thereby improving the accuracy of determining the transaction geographical location of the second category of merchants.

[0050] If the distance value of a merchant in the first category exceeding the preset data does not meet the distance requirement, that is, if the distance value of a merchant in the first category with the preset data is lower than the preset distance threshold, then the latitude and longitude of each merchant in the first category are determined; among the latitude and longitude of each merchant, a target latitude and longitude with the same preset number of latitude and longitude digits is determined; and the target latitude and longitude is determined as the transaction geographical location of the second category of merchants in the merchant cluster.

[0051] For example, this category cannot be directly diffused. In this case, based on the latitude and longitude of each merchant's transaction location, the precision of the latitude and longitude decimal places is determined. By reducing the decimal places, information at the merchant's country, city, etc., can be identified. For instance, the merchants in the first category are still concentrated in one county, but relatively dispersed in different areas of the county. In this case, we can determine which decimal place of their latitude and longitude will be consistent, and take that decimal place as the transaction location of the unknown merchant. In Table 1 below, based on the location of the first three merchant accounts (C), 100004 is located as 98.12 and 112.12.

[0052] Table 1

[0053] UserID Transaction Location 100001 98.12345678，112.12345678 100002 98.12456789，112.12456789 100003 98.12567890，112.12567890 100004 98.12，112.12

[0054] As an optional implementation, if the merchant cluster is determined by user overlap, the transaction geographical location of the first type of merchant with the highest overlap can also be determined and used as the transaction geographical location of the second type of merchant.

[0055] As can be seen, this embodiment fully utilizes transaction associations to determine the relationships between merchants from dimensions such as user overlap, device association, and WIFIMAC association, forming merchant clusters. Then, it transmits the known transaction geographical locations within the merchant clusters to merchants with unknown transaction geographical locations, greatly improving the transaction geographical location acquisition rate and accuracy of transaction nodes.

[0056] As an optional implementation, if merchants in the merchant clusters identified through the above three methods share the same unknown transaction geographical location, the transaction geographical location of that merchant will be determined based on the first type of merchant in each cluster. This will result in the merchant receiving three relatively accurate transaction geographical locations. However, since the unknown transaction geographical locations determined by the three methods may differ, to further refine the merchant's transaction geographical location, the following processing method is employed: the average of the merchant's three transaction geographical location addresses is obtained, and this average is used as the merchant's final transaction geographical location, thus yielding a more accurate transaction geographical location.

[0057] In one or more embodiments of this specification, merchant clusters with related transactions are identified from a merchant group. Each merchant in a cluster has transactional relationships and their transaction locations are close. Therefore, a first category of merchants with known transaction geographical locations is identified, and the transaction geographical locations of a second category of merchants are further determined based on this. By mining the related information within the same merchant cluster, the purpose of transmitting and disseminating transaction geographical locations among merchants is achieved. Since the first and second categories of merchants in a merchant cluster have related transactions and their transaction locations are close, determining the transaction geographical locations of the second category of merchants based on the first category of merchants can improve the accuracy of the transaction geographical locations of the second category of merchants. In cases where the transaction geographical location is empty, this embodiment can fill in the missing locations to compensate for the lack of known or accurate transaction geographical locations of the second category of merchants.

[0058] Furthermore, in the process of disseminating the geographical location of transactions, this embodiment fully utilizes the information value brought by the decimal places of latitude and longitude. When the accuracy is insufficient, by reducing the decimal places of latitude and longitude, information of different dimensions such as the merchant's country and city can be restored, thereby improving the accuracy of merchants with unknown transaction geographical locations and creating significant value in practical applications.

[0059] As an optional embodiment, after determining the transaction geographical location of the second type of merchants in the merchant cluster, the transaction geographical location of the new merchant in the merchant cluster is obtained; the transaction geographical location of the new merchant is then calibrated using the transaction geographical location of the merchant cluster. If the transaction geographical location of the new merchant differs from that of the first type of merchants in the merchant cluster, the transaction geographical location of the new merchant is determined based on the transaction geographical location of the first type of merchants.

[0060] As an optional embodiment, after determining the transaction geolocation of the second type of merchants in the merchant cluster, the merchants who transacted with the user are obtained; the transaction geolocation of the merchants who transacted with the user is used as the user's transaction geolocation. Specifically, the transaction geolocation of the merchants can be sent to the user's account to locate the user's transaction geolocation.

[0061] For example, in a QR code scanning scenario, there are two types of transactions: Merchant B scanning User C and User C scanning Merchant B. The C-to-B payment process is as follows: the user opens the app, scans the code and is redirected to the payment interface, enters the payment amount, selects the payment method, and enters the payment password to complete the payment. Since this process is primarily completed by the user, the system can collect the specific location of the transaction as long as the user does not actively disable transaction geolocation. The B-to-C payment process is relatively simple. Usually, the user only needs to open the app and show the payment code to complete the payment. In some cases, the user can even complete the payment without opening the app by directly retrieving the payment code. However, this process usually does not collect the actual transaction geolocation. In this case, the transaction geolocation of the user is often obtained by tracing back to the previous transaction geolocation within a certain period. Therefore, the accuracy of the B-to-C transaction geolocation is relatively low. Since the merchant's location is relatively fixed, obtaining the transaction geolocation of the second type of merchant can be used as the transaction geolocation of the user, thus improving the accuracy of the user's transaction geolocation.

[0062] Furthermore, one or more methods of this embodiment can be used in scenarios where internal codes are used externally, that is, when a merchant's QR code registered in China is used abroad and the transaction occurs abroad, this solution also applies.

[0063] Based on the same inventive concept, this embodiment provides a geographic location processing system. Similar or identical parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments.

[0064] See Figure 2 The geographic location processing system of this embodiment includes:

[0065] The first determining unit 200 is used to determine the merchant clusters with transaction associations from the merchant group;

[0066] The second determining unit 202 is used to determine a first type of merchant from the merchant cluster; the first type of merchant is a merchant in the merchant cluster whose transaction geographical location is known.

[0067] The third determining unit 204 is used to determine the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster; wherein the second type of merchants are merchants whose transaction geographical location is unknown in the merchant cluster.

[0068] As an optional embodiment, the merchant groups are divided according to the following method:

[0069] Merchants are categorized based on their registered location to obtain the aforementioned merchant groups; or

[0070] The merchant transaction addresses of the merchants are divided according to preset geographical regions to obtain the merchant groups.

[0071] As an optional embodiment, the first determining unit 200 specifically includes:

[0072] The fourth determining unit is used to determine the set of merchants with transaction data from the merchant group;

[0073] The first acquisition unit is used to acquire the user overlap degree of each trading merchant in the trading merchant set; the user overlap degree of each trading merchant is used to characterize the degree to which each trading merchant and each of the remaining trading merchants in the trading merchant set, excluding that trading merchant, have the same trading users;

[0074] The fifth determining unit is used to determine the merchant cluster based on the user overlap of all merchants in the merchant set.

[0075] As an optional embodiment, the first acquisition unit specifically includes:

[0076] The first acquisition subunit is used to acquire, for each trading merchant in the trading merchant set, the first number of users with the same trading users in the trading merchant and each remaining trading merchant, and the second number of users combined in the trading merchant and each remaining trading merchant.

[0077] The second acquisition subunit is used to obtain the user overlap between the trading merchant and each remaining trading merchant based on the first user count and the second user count.

[0078] As an optional embodiment, the first determining unit 200 is specifically used for:

[0079] Within the merchant group, several merchants who have used the same device and its associated account are identified as the merchant cluster; or

[0080] Within the merchant group, several merchants who have used accounts corresponding to the same MAC address are identified as the merchant cluster.

[0081] As an optional embodiment, the third determining unit 204 is specifically used to determine the merchant distance value of all merchants in the first type of merchants based on the transaction geographical location of all merchants in the first type of merchants; the merchant distance value is used to characterize the relative distance between any two merchants in the first type of merchants; if the merchant distance value of the first type of merchants exceeds the preset data and meets the distance requirement, the average transaction geographical location of the first type of merchants is determined as the transaction geographical location of the second type of merchants in the merchant cluster.

[0082] As an optional embodiment, the third determining unit 204 is specifically used for:

[0083] If the distance value of a merchant in the first type of merchant exceeds the preset data does not meet the distance requirement, determine the latitude and longitude of each merchant in the first type of merchant.

[0084] Among the latitude and longitude coordinates of each merchant, a target latitude and longitude coordinate with the same number of digits in a preset range is determined;

[0085] The target latitude and longitude are determined as the transaction geographical location of the second type of merchant in the merchant cluster.

[0086] As an optional embodiment, the system further includes:

[0087] The second acquisition unit is used to acquire the transaction geographical location of new merchants in the merchant cluster;

[0088] A calibration unit is used to calibrate the transaction geographical location of the new merchant using the transaction geographical location of the first type of merchant.

[0089] As an optional embodiment, the system further includes:

[0090] The third acquisition unit is used to acquire merchants who have transacted with the user; and to use the transaction geographical location of the merchants who have transacted with the user as the transaction geographical location of the user.

[0091] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0092] Based on the same inventive concept as in the foregoing embodiments, this specification also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0093] Based on the same inventive concept as in the foregoing embodiments, embodiments of this specification also provide a computer device, such as... Figure 3 As shown, it includes a memory 304, a processor 302, and a computer program stored in the memory 304 and executable on the processor 302. When the processor 302 executes the program, it implements the steps of any of the methods described above.

[0094] Among them, Figure 3In this document, a bus architecture (represented by bus 300) is used. Bus 300 may include any number of interconnected buses and bridges, linking various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 304. Receiver 301 and transmitter 304 may be the same element, i.e., a transceiver, providing a unit for communicating with various other terminal devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 can be used to store data used by processor 302 during operation.

[0095] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is readily apparent from the above description. Furthermore, this specification is not directed to any particular programming language. It should be understood that the contents of this specification can be implemented using various programming languages, and the above descriptions of specific languages ​​are for the purpose of disclosing implementation methods.

[0096] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this specification may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0097] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various inventive aspects, in the foregoing description of exemplary embodiments of this specification, various features of this specification are sometimes grouped together in a single embodiment, figure, or description thereof. However, this approach to disclosure should not be construed as reflecting an intention that the claimed specification requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this specification.

[0098] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0099] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of this specification and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0100] The various component embodiments of this specification can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components of the gateway, proxy server, or system according to embodiments of this specification. This specification can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing some or all of the methods described herein. Such implementations of this specification can be stored on a computer-readable medium or can take the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0101] It should be noted that the above embodiments are illustrative of this specification and not limiting of it, and that alternative embodiments can be devised by those skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This specification can be implemented by means of hardware comprising different elements and by means of a suitably programmed computer. In the unit claims enumerating means, each of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

Claims

1. A method for processing geographic location, the method comprising: Identifying merchant clusters with transaction associations from a merchant group specifically includes: identifying merchant clusters with transaction associations within a preset time interval from the merchant group; wherein, the merchant clusters having associated transactions means that each merchant in the merchant cluster has associated attributes during transactions with users, and the associated attributes include: the same transaction object, or transactions using accounts on the same device, or transactions using accounts corresponding to the same MAC address; A first category of merchants is determined from the merchant cluster; the first category of merchants are those whose transaction geographical locations are known within the merchant cluster. Based on the transaction geographical location of the first type of merchants in the merchant cluster, the transaction geographical location of the second type of merchants in the merchant cluster is determined; the second type of merchants are those whose transaction geographical location is unknown in the merchant cluster.

2. The method as described in claim 1, wherein the merchant groups are divided according to the following method: Merchants are categorized based on their registered location to obtain the aforementioned merchant groups; or The merchant transaction addresses of the merchants are divided according to preset geographical regions to obtain the merchant groups.

3. The method as described in claim 1, wherein determining the merchant cluster with transaction association from the merchant group specifically includes: From the merchant group, identify the set of merchants with transaction data; Obtain the user overlap rate for each merchant in the aforementioned merchant set; The user overlap of each trading merchant is used to characterize the degree to which each trading merchant and each of the remaining trading merchants in the trading merchant set, excluding that trading merchant, have the same trading users; The merchant cluster is determined based on the user overlap of all merchants in the merchant set.

4. The method as described in claim 3, wherein obtaining the user overlap rate of each merchant in the merchant set specifically includes: For each trading merchant in the trading merchant set, obtain the first number of users with the same trading users in that trading merchant and each remaining trading merchant, and obtain the second number of users combined in that trading merchant and each remaining trading merchant; Based on the first number of users and the second number of users, the user overlap between the trading merchant and each of the remaining trading merchants is obtained.

5. The method as described in claim 1, wherein determining the merchant cluster with transaction association from the merchant group specifically includes: Within the merchant group, several merchants who have used the same device and its corresponding account are identified as the merchant cluster; or Within the merchant group, several merchants who have used accounts corresponding to the same MAC address are identified as the merchant cluster.

6. The method as described in claim 4 or 5, wherein determining the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster specifically includes: Based on the transaction geographical location of all merchants in the first category of merchants, determine the merchant distance value of all merchants in the first category of merchants; The merchant distance value is used to characterize the relative distance between any two merchants in the first type of merchants; If the distance value of a merchant in the first type of merchant exceeds the preset data and meets the distance requirement, the average transaction geographical location of the first type of merchant is determined as the transaction geographical location of the second type of merchant in the merchant cluster.

7. The method as described in claim 6, wherein determining the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster specifically includes: If the distance value of a merchant in the first type of merchant exceeds the preset data does not meet the distance requirement, determine the latitude and longitude of each merchant in the first type of merchant. Among the latitude and longitude coordinates of each merchant, a target latitude and longitude coordinate with the same number of digits in a preset range is determined; The target latitude and longitude are determined as the transaction geographical location of the second type of merchant in the merchant cluster.

8. The method as described in claim 1, wherein after determining the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster, the method further comprises: Obtain the transaction geographical location of new merchants in the merchant cluster; The transaction geographic location of the new merchant is calibrated using the transaction geographic location of the first type of merchant.

9. The method of claim 1, wherein after determining the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster, the method further comprises: Acquire merchants who transact with users; The transaction geolocation of the merchant with whom the user transacts is used as the user's transaction geolocation.

10. A geographic location processing system, comprising: The first determining unit is used to determine the merchant clusters with transaction associations from the merchant group, specifically including: determining the merchant clusters with transaction associations within a preset time interval from the merchant group; wherein, the associated transaction refers to the association attribute between each merchant in the merchant cluster and the user during the transaction process, and the association attribute includes: the same transaction object, or the transaction using the same device account, or the transaction using the same MAC address account. The second determining unit is used to determine a first type of merchant from the merchant cluster; the first type of merchant is a merchant in the merchant cluster whose transaction geographical location is known. The third determining unit is used to determine the transaction geographical location of the second type of merchants in the merchant cluster based on the transaction geographical location of the first type of merchants in the merchant cluster; wherein the second type of merchants are merchants whose transaction geographical location is unknown in the merchant cluster.

11. The system of claim 10, wherein the merchant groups are divided according to the following method: Merchants are categorized based on their registered location to obtain the aforementioned merchant groups; or The merchant transaction addresses of the merchants are divided according to preset geographical regions to obtain the merchant groups.

12. The system of claim 10, wherein the first determining unit specifically includes: The fourth determining unit is used to determine the set of merchants with transaction data from the merchant group; The first acquisition unit is used to acquire the user overlap degree of each trading merchant in the trading merchant set; the user overlap degree of each trading merchant is used to characterize the degree to which each trading merchant and each of the remaining trading merchants in the trading merchant set have the same trading users; The fifth determining unit is used to determine the merchant cluster based on the user overlap of all merchants in the merchant set.

13. The system of claim 12, wherein the first acquisition unit specifically includes: The first acquisition subunit is used to acquire, for each merchant in the merchant set, the number of first users with the same trading users in the merchant set and each remaining merchant, and the number of second users combined in the merchant set and each remaining merchant. The second acquisition subunit is used to obtain the user overlap between the trading merchant and each remaining trading merchant based on the first user count and the second user count.

14. The system of claim 10, wherein the first determining unit is specifically configured to: Within the merchant group, several merchants who have used the same device and its associated account are identified as the merchant cluster; or Within the merchant group, several merchants who have used accounts corresponding to the same MAC address are identified as the merchant cluster.

15. The system as described in claim 13 or 14, wherein the third determining unit is specifically configured to determine the merchant distance value of all merchants in the first category of merchants based on the transaction geographical location of all merchants in the first category of merchants; the merchant distance value is used to characterize the relative distance between any two merchants in the first category of merchants; if the merchant distance value of the first category of merchants exceeds a preset data and meets the distance requirement, the average transaction geographical location of the first category of merchants is determined as the transaction geographical location of the second category of merchants in the merchant cluster.

16. The system of claim 15, wherein the third determining unit is specifically used for: If the distance value of a merchant in the first type of merchant exceeds the preset data does not meet the distance requirement, determine the latitude and longitude of each merchant in the first type of merchant. Among the latitude and longitude coordinates of each merchant, a target latitude and longitude coordinate with the same number of digits in a preset range is determined; The target latitude and longitude are determined as the transaction geographical location of the second type of merchant in the merchant cluster.

17. The system of claim 10, further comprising: The second acquisition unit is used to acquire the transaction geographical location of new merchants in the merchant cluster; A calibration unit is used to calibrate the transaction geographical location of the new merchant using the transaction geographical location of the first type of merchant.

18. The system of claim 10, further comprising: The third acquisition unit is used to acquire merchants who transact with users; The transaction geolocation of the merchant with whom the user transacts is used as the user's transaction geolocation.

19. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method according to any one of claims 1-9.

20. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, performs the steps of the method according to any one of claims 1-9.

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