Method, device, equipment, medium and program product for determining geographic location information

Abstract

This application relates to a method, apparatus, computer device, storage medium, and computer program product for determining geographic location information. The method includes: obtaining target anonymous online transaction data and business scenario information associated with the target anonymous online transaction data; and determining target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information; matching the target attribute information with information stored in a target cache; and determining the geographic location information of the target anonymous user based on the matched information if the match is successful. If the match is unsuccessful, matching the target attribute information with information stored in a target retriever and determining the geographic location information of the target anonymous user based on the matched information. This method can be used to manage anonymous customers.

Description

Technical Field

[0001] The present application relates to the technical field of big data intelligent analysis, and in particular to a transaction area determination method, device, storage medium and computer program product. Background Art

[0002] In financial services, financial institutions have branches or subsidiaries that manage and serve their customers. Generally speaking, financial institutions determine the customer's geographic region based on their location information, categorize customers by region, and assign corresponding branches or subsidiaries to provide targeted services and management to customers within that region.

[0003] In the prior art, generally speaking, financial institutions will record the bank branch information of customers when they open electronic channels in their own financial systems, determine the customer's geographical location based on the bank branch information, and divide customers according to the geographical location to facilitate customer management and targeted services.

[0004] However, a large number of customers, often referred to as anonymous customers, open electronic channels through online registration rather than visiting a bank branch. Because financial institutions lack access to anonymous customers' geographic locations, they fail to further categorize them, hindering their management. Summary of the Invention

[0005] Based on this, it is necessary to provide a method, apparatus, computer device, storage medium and computer program product for determining geographic location information of anonymous customers to address the above technical issues, so as to manage anonymous customers.

[0006] In a first aspect, a method for determining geographic location information is provided, the method comprising:

[0007] Obtaining target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determining target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information;

[0008] Matching target attribute information with information stored in a target buffer, wherein the target buffer stores attribute information of anonymous users corresponding to a geographical location with the largest number of anonymous online transactions during a target historical time period;

[0009] If the match is successful, the geographic location information of the target anonymous user is determined based on the matched information;

[0010] If the match is unsuccessful, the target attribute information is matched with the information stored in the target retriever, and the geographic location information of the target anonymous user is determined based on the matched information, wherein the target retriever stores multiple sets of correspondences between the anonymous user's attribute information and the geographic location area.

[0011] In one embodiment, obtaining target anonymous online transaction data includes:

[0012] Obtain multiple anonymous online transaction data within a preset time period;

[0013] According to a preset priority setting method, priority information of each anonymous online transaction data is determined, and according to the priority information, the anonymous online transaction data with the highest priority is selected as the target anonymous online transaction data.

[0014] In one embodiment, before determining the priority information of each anonymous online transaction data according to a preset priority setting method, the method further includes:

[0015] Obtaining attribute information of an anonymous user corresponding to each anonymous online transaction data, and performing filtering processing on each anonymous online transaction data based on the attribute information of the anonymous user corresponding to each anonymous online transaction data, so as to filter out anonymous online transaction data having illegal attribute information from the plurality of anonymous online transaction data;

[0016] Correspondingly, according to the preset priority setting method, the priority information of each anonymous online transaction data is determined, including:

[0017] According to a preset priority setting method, priority information of each anonymous online transaction data obtained after filtering is determined.

[0018] In one embodiment, matching target attribute information with information stored in a target cache includes:

[0019] Determining a target attribute category corresponding to the target attribute information;

[0020] A target cache is determined from a plurality of caches according to a target attribute category, wherein each cache corresponds to a different attribute category and each cache stores attribute information of anonymous users in a target geographic location area that is consistent with the attribute category corresponding to each cache.

[0021] In one embodiment, matching target attribute information with information stored in a target retriever includes:

[0022] According to the target attribute category, a target retriever is determined from multiple retrievers, wherein each retriever corresponds to a different attribute category, and each retriever stores multiple sets of correspondences between attribute information of anonymous users consistent with the attribute category corresponding to each retriever and geographic location.

[0023] In one embodiment, before obtaining the target anonymous online transaction data and the business scenario information of the target anonymous online transaction data, the process further includes:

[0024] Acquire multiple historical anonymous online transaction data within a target historical time period and attribute information of anonymous users corresponding to each historical anonymous online transaction data;

[0025] For each piece of historical anonymous online transaction data, the attribute information of the anonymous user corresponding to each piece of historical anonymous online transaction data is matched with the information in each search engine to obtain the historical geographical location area corresponding to each piece of historical anonymous online transaction data;

[0026] Collect statistics on the historical anonymous online transaction data corresponding to each historical geographic location area, and select the historical geographic location area with the largest number of anonymous online transactions during the target historical time period as the target historical geographic location area;

[0027] The attribute category corresponding to each retriever and the storage information corresponding to the target historical geographic location area in each retriever are obtained, and the storage information is batch loaded into a cache having the same attribute category as the retriever.

[0028] In one embodiment, after batch loading the search information corresponding to the geographical location areas in each searcher into the corresponding cache according to the attribute category, the method includes:

[0029] Determine whether there is duplicate attribute information of anonymous users stored in the cache;

[0030] If there is duplicated attribute information of anonymous users, the information to be retained is determined according to the time when the attribute information of each anonymous user is loaded into the cache, and the cache is updated according to the information to be retained.

[0031] In one embodiment, the method further comprises:

[0032] detecting whether a trigger instruction of the buffer is satisfied, and determining update information of the buffer if the trigger instruction is satisfied;

[0033] The buffer is updated according to the update information of the buffer.

[0034] In a second aspect, a device for determining geographic location information is provided, the device comprising:

[0035] an acquisition module, configured to acquire target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determine target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information;

[0036] a first matching module for matching target attribute information with information stored in a target buffer, wherein the target buffer stores attribute information corresponding to anonymous users in a geographical location with the largest number of anonymous online transactions during a target historical time period, and, if a match is successful, determining the geographical location information of the target anonymous user based on the matched information;

[0037] The second matching module is used to match the target attribute information with the information stored in the target retriever when the target attribute information fails to match the information stored in the target cache, and determine the geographic location information of the target anonymous user based on the matched information, wherein the target retriever stores multiple sets of correspondences between the anonymous user's attribute information and the geographic location area.

[0038] In one embodiment, the acquisition module includes:

[0039] A data acquisition unit, configured to acquire a plurality of anonymous online transaction data within a preset time period;

[0040] The priority setting unit is used to determine the priority information of each anonymous online transaction data according to a preset priority setting method, and select the anonymous online transaction data with the highest priority as the target anonymous online transaction data according to the priority information.

[0041] In one embodiment, the device further comprises a filtering module, specifically:

[0042] a filtering module configured to obtain attribute information of an anonymous user corresponding to each anonymous online transaction data, and perform filtering processing on each anonymous online transaction data based on the attribute information of the anonymous user corresponding to each anonymous online transaction data, so as to filter out anonymous online transaction data having illegal attribute information from the plurality of anonymous online transaction data;

[0043] Correspondingly, the priority setting unit is used to determine the priority information of each anonymous online transaction data obtained after filtering according to a preset priority setting method.

[0044] In one embodiment, the first matching module is specifically configured to:

[0045] Determining a target attribute category corresponding to the target attribute information;

[0046] A target cache is determined from a plurality of caches according to a target attribute category, wherein each cache corresponds to a different attribute category and each cache stores attribute information of anonymous users in a target geographic location area that is consistent with the attribute category corresponding to each cache.

[0047] In one embodiment, the second matching module is specifically configured to:

[0048] According to the target attribute category, a target retriever is determined from multiple retrievers, wherein each retriever corresponds to a different attribute category, and each retriever stores multiple sets of correspondences between attribute information of anonymous users consistent with the attribute category corresponding to each retriever and geographic location.

[0049] In one embodiment, the device further includes a loading module, the loading module including:

[0050] A historical data unit, used to obtain multiple historical anonymous online transaction data within a target historical time period and attribute information of anonymous users corresponding to each historical anonymous online transaction data;

[0051] A data matching unit is used to match the attribute information of the anonymous user corresponding to each historical anonymous online transaction data with the information in each search engine to obtain the historical geographical location area corresponding to each historical anonymous online transaction data;

[0052] a data statistics unit for collecting statistics on historical anonymous online transaction data corresponding to each historical geographic location area, and defining the historical geographic location area with the largest number of anonymous online transactions during the target historical time period as the target historical geographic location area;

[0053] The data loading unit is used to obtain the attribute category corresponding to each retriever and the storage information corresponding to the target historical geographical location area in each retriever, and load the storage information in batches into a cache with the same attribute category as the retriever.

[0054] In one embodiment, the apparatus further includes an update module, wherein the update module is configured to:

[0055] Determine whether there is duplicate attribute information of anonymous users stored in the cache;

[0056] If there is duplicated attribute information of anonymous users, the information to be retained is determined according to the time when the attribute information of each anonymous user is loaded into the cache, and the cache is updated according to the information to be retained.

[0057] In one embodiment, the apparatus further includes an updating module, wherein the triggering module is configured to:

[0058] detecting whether a trigger instruction of the buffer is satisfied, and determining update information of the buffer if the trigger instruction is satisfied;

[0059] The buffer is updated according to the update information of the buffer.

[0060] In a third aspect, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for determining geographic location information as described in the first aspect above is implemented.

[0061] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for determining geographic location information as described in the first aspect above is implemented.

[0062] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method for determining geographic location information as described in any one of the first aspects above.

[0063] The above-mentioned geographic location information determination method, device, computer equipment, storage medium and computer program product obtain target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determine the target attribute information of the target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information; match the target attribute information with the information stored in the target cache, wherein the target cache stores the attribute information of the anonymous users corresponding to the geographic location area with the largest number of anonymous online transactions in the target historical time period; if the match is successful, the geographic location information of the target anonymous user is determined based on the matched information; if the match is unsuccessful, the target attribute information is matched with the information stored in the target retriever, and the geographic location information of the target anonymous user is determined based on the matched information, wherein the target retriever stores multiple sets of correspondences between the attribute information of the anonymous user and the geographic location area. By obtaining the target attribute information of the target anonymous user corresponding to the target anonymous online transaction data, and using the target attribute information to match with the information in the cache and the retriever in turn, the geographic location information of the target anonymous user is obtained, and the geographical area of ​​the anonymous customer is determined, so as to facilitate the management of the anonymous customer; in addition, since the information stored in the target cache is smaller than the information stored in the target retriever, the target attribute information is first matched with the information stored in the target cache, and then only the target attribute information that cannot be matched with the information stored in the target cache is matched with the information stored in the target cache. Compared with directly matching all the target attribute information with the information in the target retriever, the data processing amount for executing information matching can be reduced, the execution efficiency of information matching and the efficiency of determining geographic location information are improved, which is more conducive to the management of anonymous customers. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 1 is a flow chart of a method for determining geographic location information in one embodiment;

[0065] Figure 2 101 is a flow chart of step 101 in one embodiment;

[0066] Figure 3 This is an example diagram of a method for determining geographic location information in one embodiment;

[0067] Figure 4 102 is a flow chart of step 102 in one embodiment;

[0068] Figure 5 1 is a flow chart of a method for determining geographic location information in one embodiment;

[0069] Figure 6 This is an example diagram of a method for determining geographic location information in one embodiment;

[0070] Figure 7 1 is a flow chart of a method for determining geographic location information in one embodiment;

[0071] Figure 8 1 is a flow chart of a method for determining geographic location information in one embodiment;

[0072] Figure 9 1 is a flow chart of a method for determining geographic location information in one embodiment;

[0073] Figure 10 is a structural block diagram of a device for determining geographic location information in one embodiment;

[0074] Figure 11 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0075] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0076] In financial services, financial institutions have branches or subsidiaries that manage and serve their customers. Generally speaking, financial institutions determine the customer's geographic region based on their location information, categorize customers by region, and assign corresponding branches or subsidiaries to provide targeted services and management to customers within that region.

[0077] Electronic banking channels include online banking, telephone banking, mobile banking, and other services utilizing electronic devices and networks. Customers use these channels to conduct financial transactions in a self-service manner. There are two ways to activate electronic banking services: by visiting a bank branch or by registering online.

[0078] In the prior art, financial institutions record the bank branch information of customers when they open electronic channels in their own financial systems, determine the customer's geographical location based on the bank branch information, and divide customers according to the geographical location to facilitate customer management.

[0079] However, a large number of customers, often referred to as anonymous customers, open electronic channels through online registration rather than visiting a bank branch. Because financial institutions lack access to anonymous customers' geographic locations, they fail to further categorize them, hindering their management.

[0080] In view of this, an embodiment of the present application provides a method for determining geographic location information, which realizes the determination of the geographic location of an anonymous customer, so as to facilitate the management of the anonymous customer.

[0081] It should be noted that the execution subject of the geographic location information determination method provided in the embodiment of the present application can be a geographic location information determination device, and the geographic location information determination device can be implemented as part or all of the terminal through software, hardware, or a combination of software and hardware.

[0082] In the following method embodiments, the execution subject is described as a terminal as an example, wherein the terminal can be a personal computer, a laptop computer, a media player, a smart TV, a smart phone, a tablet computer, and a portable wearable device, etc. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server.

[0083] Please refer to Figure 1 , which shows a flow chart of a method for determining geographic location information provided by an embodiment of the present application. Figure 1 As shown, the method for determining geographic location information includes the following steps:

[0084] Step 101 : Obtain target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determine target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information.

[0085] The target anonymous online transaction data includes the target anonymous user's transaction flow, withdrawal transaction data, balance inquiry data, etc.

[0086] The target attribute information includes at least one of an IP address, a mobile phone number, and an employer. Business scenario information includes business scenarios that use mobile phone numbers as attribute information, such as mobile phone registration / login scenarios, and business scenarios that use IP addresses as attribute information, such as computer-based registration / login scenarios. In this case, because anonymous users do not bind their mobile phone numbers during registration / login, IP addresses are used as attribute information.

[0087] Optionally, the terminal divides the anonymous online transaction data into two business scenarios, namely, PC and mobile, based on the type of device used by the anonymous user when generating the anonymous online transaction data. When the terminal receives the target anonymous online transaction data, it detects the device used by the anonymous user and, based on the device type information, obtains the business scenario information for the target anonymous online transaction data.

[0088] Optionally, a mapping relationship between business scenario information and target attribute information is set in the terminal. After obtaining the business scenario information, the terminal determines the target attribute information by looking up a table.

[0089] Step 102: Match the target attribute information with the information stored in the target cache.

[0090] The target buffer stores attribute information of anonymous users corresponding to the geographical location area where the largest number of anonymous online transactions occurred during the target historical time period.

[0091] The anonymous user's attribute information includes the anonymous user's IP address, mobile phone number, or workplace, etc. The target buffer includes the attribute information, the geographical location area corresponding to the attribute information, the area postal code information, and the bank outlet / branch code information, etc.

[0092] Optionally, the geographical location area, postal code, and bank branch code may be used to generate an MD5 encoding value using the MD5 message digest algorithm.

[0093] Optionally, a cache area is provided in the terminal, and the cache area is divided into a plurality of areas according to the number of categories of attribute information, and a cache is provided corresponding to each area.

[0094] Optionally, the target attribute information is matched with the attribute information in the target buffer using an information matching algorithm, for example, a KMP matching algorithm.

[0095] Step 103: If the match is successful, the geographic location information of the target anonymous user is determined based on the matched information.

[0096] The geographic location information includes geographic location area, regional postal code information, bank outlet / branch code information, etc.

[0097] Optionally, when the target attribute information successfully matches the attribute information in the target cache, the attribute information is used to obtain a corresponding MD5 encoding value, and then the MD5 encoding value is decoded to obtain the corresponding geographic location information.

[0098] Step 104: If the matching is unsuccessful, the target attribute information is matched with the information stored in the target retriever, and the geographic location information of the target anonymous user is determined based on the matched information.

[0099] The target retriever stores multiple sets of correspondences between anonymous user attribute information and geographical location areas, including geographical location areas, regional postal code information, and bank outlet / branch code information.

[0100] Optionally, a specific storage area is provided in the terminal for storing data in the retriever, and the specific storage area is divided into multiple areas according to the number of categories of attribute information, and each area is correspondingly provided with a retriever.

[0101] The specific matching method is the same as that in step 102 and will not be described in detail here.

[0102] This embodiment obtains the target attribute information of the target anonymous user corresponding to the target anonymous online transaction data, and uses the target attribute information to match the information in the cache and the retriever in sequence to obtain the geographic location information of the target anonymous user, thereby determining the geographic area of ​​the anonymous customer, so as to facilitate the management of the anonymous customer. In addition, since the information stored in the target cache is smaller than the information stored in the target retriever, the target attribute information is first matched with the information stored in the target cache, and then only the target attribute information that cannot be matched with the information stored in the target cache is matched with the information stored in the target cache. Compared with directly matching all target attribute information with the information in the target retriever, this embodiment can reduce the data processing amount for executing information matching, improve the execution efficiency of information matching and the efficiency of determining geographic location information, and is more conducive to the management of anonymous customers.

[0103] In the implementation of this application, if Figure 2 As shown, based on Figure 1 The embodiment shown in this embodiment involves obtaining target anonymous online transaction data in step 101, including steps 201 and 202:

[0104] Step 201: Acquire multiple anonymous online transaction data within a preset time period.

[0105] The preset time period may refer to a time period that ends at the current time in terms of time sequence. The length of the time period may be adjusted according to the real-time situation. For example, the length of the time period may be set to 5 seconds.

[0106] Optionally, the server stores the customer's online transaction data. The terminal sets a sampling interval according to the length of a preset time period and loads the corresponding anonymous online transaction data from the server at regular intervals.

[0107] Optionally, to avoid a large number of requests overloading the server and causing it to become unavailable, such as Figure 3 As shown, it can be used Figure 3 The flow limiter limits the transaction flow of the server during a preset time period. To prevent attacks on the online transaction data on the server, the online transaction data on the server can be encrypted and token-checked.

[0108] Optionally, a list of non-anonymous customers is stored on the server, and the online transaction data of customers not on the list can be determined as anonymous online transaction data.

[0109] In step 202 , priority information of each anonymous online transaction data is determined according to a preset priority setting method, and based on the priority information, the anonymous online transaction data with the highest priority is selected as the target anonymous online transaction data.

[0110] Optionally, the preset priority setting method includes manual setting and automatic setting. The priority level can be set according to the type of financial business corresponding to the online transaction data, wherein the financial business type is divided according to the level of real-time requirements of the online transaction.

[0111] Specifically, the manual setting method includes the financial institution personnel inputting the priority level corresponding to each integrated business type or inputting the integrated business type that needs priority response on the terminal interface.

[0112] Specifically, the automatic setting method includes storing a mapping relationship between financial service types and priority levels in the terminal, wherein the higher the real-time requirement level of the financial service type, the higher the corresponding priority level.

[0113] Optionally, when multiple priority levels are included, the anonymous online transaction data are sorted according to the priority levels, the anonymous online transaction data are retrieved in sequence, and the retrieved anonymous online transaction data are determined as target anonymous online transaction data.

[0114] Optional, such as Figure 3 As shown in , after the transaction distributor determines the target anonymous online transaction data according to the preset priority setting method, it will pass the target anonymous online transaction data to the cache to perform the process of determining the geographical location of the anonymous customer.

[0115] The embodiment of the present application obtains multiple anonymous online transaction data within a preset time period, determines the priority information of each anonymous online transaction data according to a preset priority setting method, and selects the anonymous online transaction data with the highest priority as the target anonymous online transaction data based on the priority information. By obtaining the target anonymous online transaction data in order of priority, the efficiency of the algorithm for subsequent geographic location positioning is improved and the system pressure is reduced.

[0116] In this application example, based on Figure 2 The embodiment shown in this example involves the steps before step 102 of determining the priority information of each anonymous online transaction data according to a preset priority setting method, including the following steps:

[0117] Attribute information of the anonymous user corresponding to each anonymous online transaction data is obtained, and based on the attribute information of the anonymous user corresponding to each anonymous online transaction data, filtering processing is performed on each anonymous online transaction data to filter out anonymous online transaction data with illegal attribute information from multiple anonymous online transaction data.

[0118] Optionally, the filtering processing method includes performing parameter verification and permission verification on the anonymous online transaction data, wherein the parameter verification includes checking whether the attribute information is standardized.

[0119] The embodiment of the present application obtains the attribute information of the anonymous user corresponding to each anonymous online transaction data, and performs filtering processing on each anonymous online transaction data based on the attribute information of the anonymous user corresponding to each anonymous online transaction data, thereby reducing the computational complexity of the algorithm and improving the processing efficiency of the algorithm.

[0120] In the implementation of this application, if Figure 4 As shown, based on Figure 1 The embodiment shown in FIG. 1 is related to matching the target attribute information with the information stored in the target cache in step 102, including steps 301 and 302:

[0121] Step 301: Determine the target attribute category corresponding to the target attribute information.

[0122] The target attribute type includes at least one of an IP address type, a mobile phone number type, a work unit type, and the like.

[0123] Step 302: Determine a target buffer from a plurality of buffers according to the target attribute category.

[0124] Each buffer corresponds to a different attribute category, and each buffer stores attribute information of anonymous users in the target geographical location area that is consistent with the attribute category corresponding to each buffer.

[0125] Optionally, the buffer can be expanded according to the real-time situation. Specifically, when the attribute categories increase, the number of buffers is increased accordingly.

[0126] Figure 3 The example demonstrates a scenario involving two caches: an IP cache and a mobile phone number cache. Optionally, when the target attribute information corresponding to the target anonymous online transaction data is an IP address, the IP address is matched against the information in the IP cache; when the target attribute information corresponding to the target anonymous online transaction data is a mobile phone number, the mobile phone number is matched against the information in the mobile phone number cache.

[0127] This application embodiment determines the target attribute category corresponding to the target attribute information and determines the target cache from multiple caches based on the target attribute category, thereby realizing a targeted query of the location information of the target anonymous online transaction data and improving the efficiency of information query matching in the cache.

[0128] In the embodiment of this application, based on Figure 3 In the illustrated embodiment, the process of matching the target attribute information with the information stored in the target retriever in step 104 includes: determining the target retriever from a plurality of retrievers according to the target attribute category.

[0129] Each of the retrievers corresponds to a different attribute category, and each of the retrievers stores multiple sets of correspondences between attribute information of anonymous users and geographic locations that are consistent with the attribute category corresponding to the retriever. Optionally, the number of retrievers is the same as the number of caches.

[0130] Optionally, the retrievers can be expanded horizontally based on real-time conditions. Specifically, when the number of attribute categories increases, the number of retrievers can be flexibly increased.

[0131] Similarly, refer to Figure 3 , Figure 3 The exemplary display includes two search engines: an IP database search engine and a mobile phone number search engine. Optionally, when the target attribute information corresponding to the target anonymous online transaction data is an IP address, the IP address is matched with the information in the IP search engine; when the target attribute information corresponding to the target anonymous online transaction data is a mobile phone number, the mobile phone number is matched with the information in the mobile phone number search engine.

[0132] This embodiment of the application determines the target retriever from multiple retrievers based on the target attribute category, thereby achieving a targeted query of the location information of the target anonymous online transaction data and improving the efficiency of information query matching in the retriever.

[0133] In the embodiment of this application, please refer to Figure 5 Based on the above embodiment, before obtaining the target anonymous online transaction data and the business scenario information of the target anonymous online transaction data in step 101, the geographic location information determination method further includes steps 401, 402, and 403:

[0134] Step 401: Acquire multiple historical anonymous online transaction data within a target historical time period and attribute information of anonymous users corresponding to each historical anonymous online transaction data.

[0135] The target historical time period is any time period before the preset time period. The unit of length of this time period includes day, week, month, or year.

[0136] Optionally, the target historical time period can be set to the day before or the week before the preset time period.

[0137] Step 402 : Match the attribute information of the anonymous user corresponding to each historical anonymous online transaction data with the information in each search engine to obtain the historical geographical location area corresponding to each historical anonymous online transaction data.

[0138] Optionally, for each piece of historical anonymous online transaction data, a corresponding retriever is determined based on the attribute information of the anonymous user corresponding to each piece of historical anonymous online transaction data, and the attribute information is matched with the information in the determined retriever. The specific implementation is similar to the process of matching target attribute information with the information stored in the target retriever in the above embodiment and is not further described here.

[0139] Figure 6 This example demonstrates a scenario involving two search engines: an IP database search engine and a mobile phone number search engine. The transaction distributor, based on the attribute information of historical anonymous online transaction data (i.e., IP address or mobile phone number), distributes the transaction distributor to the corresponding search engine. This process then matches the attribute information of the anonymous user corresponding to each historical anonymous online transaction data with the information in each search engine.

[0140] Optionally, when the geographical location information stored in the retriever is an MD5 encoded value, the terminal determines the MD5 encoded value corresponding to the attribute information according to the attribute information, and then decodes the MD5 encoded value to obtain the geographical location area to which the anonymous user belongs.

[0141] Step 403 : The historical geographical location area with the largest number of anonymous online transactions during the target historical time period is defined as the target historical geographical location area.

[0142] Optionally, the historical anonymous online transaction data corresponding to each historical geographic location area is counted to obtain the target historical geographic location area. Specifically, the terminal counts the historical anonymous online transaction data corresponding to the historical geographic location area to obtain the number of historical anonymous online transactions corresponding to each historical geographic location area.

[0143] Step 404: Obtain the attribute categories corresponding to each searcher and the storage information corresponding to the target historical geographic location area in each searcher, and load the storage information into the cache in batches.

[0144] The cache refers to a cache having the same attribute category as the retriever.

[0145] like Figure 6As shown in , when the monitoring module detects frequent online transactions in a certain area, it loads the search engine corresponding to that geographic location into the corresponding cache. The corresponding information in the IP library search engine is batch loaded into the IP cache; the corresponding information in the mobile phone number search engine is batch loaded into the mobile phone number cache.

[0146] Optionally, the target historical geographic location area is matched with each retriever, and the matched information is loaded into a cache having the same attribute information as the retriever.

[0147] This embodiment collects statistics on the historical anonymous online transaction data corresponding to each of the historical geographic location areas, takes the historical geographic location area with the largest number of anonymous online transactions during the target historical time period as the target historical geographic location area, obtains the attribute category corresponding to each of the retrievers and the storage information corresponding to the target historical geographic location area in each of the retrievers, and loads the storage information in batches into a cache having the same attribute category as the retriever, thereby loading the geographic location information corresponding to the high-incidence online transaction areas into the cache, thereby improving the query efficiency of the geographic location information of the high-incidence online transaction areas.

[0148] In the embodiment of this application, please refer to Figure 7 ,based on Figure 4 In the embodiment described, the method for determining geographic location information includes steps 501 and 502:

[0149] Step 501: Determine whether there is duplicate attribute information of anonymous users stored in the cache.

[0150] Optionally, the attribute information and geographic location information are stored in the cache as key-value pairs, with the attribute information set as the key value and the geographic location information set as the value. The terminal detects the key value and determines whether there are multiple key-value pairs corresponding to the key value in the cache. If so, it determines that the attribute information of the anonymous user is stored repeatedly in the cache.

[0151] Step 502: If there is duplicated stored attribute information of anonymous users, the information to be retained is determined based on the time when the attribute information of each anonymous user is loaded into the cache, and the cache is updated based on the information to be retained.

[0152] Optionally, when the terminal stores information in a key-value pair in the cache, it records the loading time of the key-value pair, which is the time it takes to load the attribute information of each anonymous user into the cache. When the terminal detects that a key value corresponds to multiple key-value pairs, it compares the loading times corresponding to the key-value pairs, determines the most recently loaded key-value pair as the information to be retained, and deletes the other key-value pairs corresponding to the key value.

[0153] This embodiment determines whether there is duplicated anonymous user attribute information stored in the cache. If there is duplicated anonymous user attribute information, the embodiment determines the information to be retained based on the time when the attribute information of each anonymous user is loaded into the cache, and updates the cache based on the information to be retained. Since the cache only needs to retain the most recently loaded information, duplicate storage of cache information is avoided, and conflicts of information in the cache are avoided.

[0154] In the embodiment of this application, please refer to Figure 8 ,based on Figure 4 In the embodiment described, the method for determining geographic location information includes steps 601 and 602:

[0155] Step 601 , detecting whether a trigger instruction of the buffer is satisfied, and determining update information of the buffer if the trigger instruction is satisfied.

[0156] The trigger instruction includes a manual trigger instruction and an automatic trigger instruction.

[0157] Optionally, a manual trigger instruction refers to an instruction to trigger the update of the cache in a manual triggering manner. A trigger button for the cache is set on the terminal interface, and the trigger instruction is that the trigger button is clicked. When the terminal detects that the trigger button is clicked, the trigger instruction of the cache is satisfied. Figure 6 As shown, the update instruction of the cache is triggered in the form of a trigger, and the management platform interface sets the relevant information of the trigger instruction.

[0158] Optionally, an automatic trigger instruction refers to automatically triggering a cache update instruction based on a set trigger condition. The trigger condition includes update time period information, such as 3 days. When the preset time period is reached, the cache update instruction is automatically triggered. Alternatively, based on the hotspot geographic location area corresponding to the hotspot data, when a change in the hotspot geographic location area is detected, the cache trigger instruction is triggered.

[0159] Optionally, the terminal is configured with a correspondence between a trigger instruction and a buffer update method. The buffer update method includes, among other things, the buffer update content and the storage method of the buffer content. When the buffer trigger instruction is satisfied, the terminal determines the update method for the trigger instruction based on the correspondence, and determines the corresponding update information for the buffer according to the update method.

[0160] Step 602: Update the cache according to the cache update information.

[0161] This embodiment detects whether the trigger instruction of the cache is satisfied, and when the trigger instruction is satisfied, determines the update information of the cache, and then updates the cache according to the update information of the cache, thereby updating the information stored in the cache and improving the efficiency of querying the geographic location of anonymous users through the cache.

[0162] In the embodiment of this application, Figure 9 As shown, a method for determining geographic location information is provided, the method comprising the following steps:

[0163] Step 701: Acquire multiple historical anonymous online transaction data within a target historical time period and attribute information of anonymous users corresponding to each historical anonymous online transaction data.

[0164] Step 702 : Match the attribute information of the anonymous user corresponding to each historical anonymous online transaction data with the information in each search engine to obtain the historical geographical location area corresponding to each historical anonymous online transaction data.

[0165] Step 703: Determine the historical geographical location area with the largest number of anonymous online transactions during the target historical time period.

[0166] Step 704: Obtain the attribute categories corresponding to each searcher and the storage information corresponding to the historical geographical location areas in each searcher, and load the storage information into the cache in batches.

[0167] The cache refers to a cache having the same attribute category as the retriever.

[0168] Step 705: determine whether there is duplicate attribute information of anonymous users stored in the cache. If so, determine the information to be retained in the cache to update the cache.

[0169] The method for determining the information to be retained in the buffer to update the buffer is: determining the information to be retained according to the time when the attribute information of each anonymous user is loaded into the buffer, and updating the buffer according to the information to be retained.

[0170] Step 706 , detecting whether the trigger instruction of the buffer is satisfied, and if satisfied, determining the update information of the buffer to update the buffer.

[0171] Step 707: Acquire multiple anonymous online transaction data within a preset time period and attribute information of anonymous users corresponding to each anonymous online transaction data.

[0172] Step 708 : Filter each anonymous online transaction data based on the attribute information of the anonymous user corresponding to each anonymous online transaction data.

[0173] The purpose of the filtering process is to filter out anonymous online transaction data having illegal attribute information from a plurality of anonymous online transaction data.

[0174] Step 709 : determining the priority information of each anonymous online transaction data obtained after filtering, and taking the anonymous online transaction data with the highest priority as the target anonymous online transaction data.

[0175] Step 710: Obtain target anonymous online transaction data and its corresponding business scenario information, and determine target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information.

[0176] Step 711: Determine the target attribute category corresponding to the target attribute information, and determine a target buffer from a plurality of buffers according to the target attribute category.

[0177] Each buffer corresponds to a different attribute category, and each buffer stores attribute information of anonymous users in the target geographical location area that is consistent with the attribute category corresponding to each buffer.

[0178] Step 712: Match the target attribute information with the information stored in the target cache.

[0179] Step 713: If the match is successful, the geographic location information of the target anonymous user is determined based on the matched information.

[0180] Step 714: If the match is unsuccessful, the target search engine is determined from multiple search engines according to the target attribute category.

[0181] Each of the retrievers corresponds to a different attribute category, and each of the retrievers stores a plurality of corresponding relationships between attribute information of anonymous users consistent with the attribute category corresponding to each of the retrievers and geographic locations.

[0182] Step 715: Match the target attribute information with the information stored in the target retriever, and determine the geographic location information of the target anonymous user based on the matched information.

[0183] This embodiment obtains target attribute information of a target anonymous user corresponding to target anonymous online transaction data and uses this target attribute information to sequentially match information in a cache and a retriever to obtain the target anonymous user's geographic location information. This allows for the determination of the anonymous customer's geographic area, facilitating management of the anonymous customer. Furthermore, because the target attribute information is first matched with information stored in the target cache to obtain the target anonymous user's geographic location information, if a match is unsuccessful, the target attribute information is then matched with information stored in the target retriever, and the target anonymous user's geographic location information is determined based on the matched information, thereby improving the efficiency of determining geographic location information.

[0184] It should be understood that although Figure 1-2 、 Figure 4-5 as well as Figure 7-9 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 1-2 、 Figure 4-5 as well as Figure 7-9 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The order of execution of these steps or stages is not necessarily one by one, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0185] In the embodiments of this application, Figure 10 As shown, a device for determining geographic location information is provided, the device comprising an acquisition module, a first matching module, and a second matching module, wherein:

[0186] an acquisition module, configured to acquire target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determine target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information;

[0187] a first matching module for matching target attribute information with information stored in a target buffer, wherein the target buffer stores attribute information corresponding to anonymous users in a geographical location with the largest number of anonymous online transactions during a target historical time period, and, if a match is successful, determining the geographical location information of the target anonymous user based on the matched information;

[0188] The second matching module is used to match the target attribute information with the information stored in the target retriever when the target attribute information fails to match the information stored in the target cache, and determine the geographic location information of the target anonymous user based on the matched information, wherein the target retriever stores multiple sets of correspondences between the anonymous user's attribute information and the geographic location area.

[0189] In one embodiment, the acquisition module includes:

[0190] A data acquisition unit, configured to acquire a plurality of anonymous online transaction data within a preset time period;

[0191] The priority setting unit is used to determine the priority information of each anonymous online transaction data according to a preset priority setting method, and select the anonymous online transaction data with the highest priority as the target anonymous online transaction data according to the priority information.

[0192] In one embodiment, the device further comprises a filtering module, specifically:

[0193] a filtering module configured to obtain attribute information of an anonymous user corresponding to each anonymous online transaction data, and perform filtering processing on each anonymous online transaction data based on the attribute information of the anonymous user corresponding to each anonymous online transaction data, so as to filter out anonymous online transaction data having illegal attribute information from the plurality of anonymous online transaction data;

[0194] Correspondingly, the priority setting unit is used to determine the priority information of each anonymous online transaction data obtained after filtering according to a preset priority setting method.

[0195] In one embodiment, the first matching module is specifically configured to:

[0196] Determining a target attribute category corresponding to the target attribute information;

[0197] A target cache is determined from a plurality of caches according to a target attribute category, wherein each cache corresponds to a different attribute category and each cache stores attribute information of anonymous users in a target geographic location area that is consistent with the attribute category corresponding to each cache.

[0198] In one embodiment, the second matching module is specifically configured to:

[0199] According to the target attribute category, a target retriever is determined from multiple retrievers, wherein each retriever corresponds to a different attribute category, and each retriever stores multiple sets of correspondences between attribute information of anonymous users consistent with the attribute category corresponding to each retriever and geographic location.

[0200] In one embodiment, the apparatus further comprises a loading module, the loading module comprising:

[0201] A historical data unit, used to obtain multiple historical anonymous online transaction data within a target historical time period and attribute information of anonymous users corresponding to each historical anonymous online transaction data;

[0202] A data matching unit is used to match the attribute information of the anonymous user corresponding to each historical anonymous online transaction data with the information in each search engine to obtain the historical geographical location area corresponding to each historical anonymous online transaction data;

[0203] a data statistics unit for collecting statistics on historical anonymous online transaction data corresponding to each historical geographic location area, and defining the historical geographic location area with the largest number of anonymous online transactions during the target historical time period as the target historical geographic location area;

[0204] The data loading unit is used to obtain the attribute category corresponding to each retriever and the storage information corresponding to the target historical geographical location area in each retriever, and load the storage information in batches into a cache with the same attribute category as the retriever.

[0205] In one embodiment, the apparatus further includes an update module, the update module being configured to:

[0206] Determine whether there is duplicate attribute information of anonymous users stored in the cache;

[0207] If there is duplicated attribute information of anonymous users, the information to be retained is determined according to the time when the attribute information of each anonymous user is loaded into the cache, and the cache is updated according to the information to be retained.

[0208] In one embodiment, the apparatus further includes an updating module, wherein the triggering module is configured to:

[0209] detecting whether a trigger instruction of the buffer is satisfied, and determining update information of the buffer if the trigger instruction is satisfied;

[0210] The buffer is updated according to the update information of the buffer.

[0211] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 11As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for determining geographic location information is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0212] Those skilled in the art will understand that Figure 11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0213] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0214] Step 101: Obtain target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determine target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information;

[0215] Step 102, matching the target attribute information with the information stored in the target cache;

[0216] Step 103: If the match is successful, the geographic location information of the target anonymous user is determined based on the matched information;

[0217] Step 104: If the matching is unsuccessful, the target attribute information is matched with the information stored in the target retriever, and the geographic location information of the target anonymous user is determined based on the matched information.

[0218] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0219] Acquire multiple anonymous online transaction data within a preset time period; determine priority information of each anonymous online transaction data according to a preset priority setting method, and select the anonymous online transaction data with the highest priority as the target anonymous online transaction data according to the priority information.

[0220] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0221] Acquire attribute information of an anonymous user corresponding to each anonymous online transaction data, and perform filtering processing on each anonymous online transaction data based on the attribute information of the anonymous user corresponding to each anonymous online transaction data, so as to filter out anonymous online transaction data with illegal attribute information from multiple anonymous online transaction data; and determine the priority information of each anonymous online transaction data obtained after filtering according to a preset priority setting method.

[0222] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0223] Determine a target attribute category corresponding to the target attribute information; determine a target cache from a plurality of caches based on the target attribute category, wherein each cache corresponds to a different attribute category, and each cache stores attribute information of anonymous users in the target geographic location area that is consistent with the attribute category corresponding to each cache.

[0224] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0225] According to the target attribute category, a target retriever is determined from multiple retrievers, wherein each retriever corresponds to a different attribute category, and each retriever stores multiple sets of correspondences between attribute information of anonymous users consistent with the attribute category corresponding to each retriever and geographic location.

[0226] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0227] Acquire multiple historical anonymous online transaction data within a target historical time period and attribute information of anonymous users corresponding to each historical anonymous online transaction data; for each historical anonymous online transaction data, match the attribute information of the anonymous users corresponding to each historical anonymous online transaction data with information in each search engine to obtain the historical geographical location area corresponding to each historical anonymous online transaction data;

[0228] Statistics are collected on the historical anonymous online transaction data corresponding to each historical geographic location area, and the historical geographic location area with the largest number of anonymous online transactions during the target historical time period is defined as the target historical geographic location area; the attribute categories corresponding to each retriever and the storage information corresponding to the target historical geographic location area in each retriever are obtained, and the storage information is batch loaded into a cache with the same attribute categories as the retriever.

[0229] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0230] Determine whether there is duplicate attribute information of anonymous users stored in the cache; if there is duplicate attribute information of anonymous users stored, determine the information to be retained based on the time when the attribute information of each anonymous user is loaded into the cache, and update the cache based on the information to be retained.

[0231] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0232] Detecting whether a trigger instruction of the buffer is satisfied, and determining update information of the buffer if the trigger instruction is satisfied; and updating the buffer according to the update information of the buffer.

[0233] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0234] In one embodiment, a computer program is provided. When the computer program is executed by a processor, the steps in the above method embodiments are also implemented.

[0235] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0236] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0237] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for determining geographic location information, characterized in that: The method comprises: Acquire target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determine target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information; Matching the target attribute information with information stored in a target buffer, wherein the target buffer stores attribute information of anonymous users corresponding to a geographical location with the largest number of anonymous online transactions during a target historical time period; The matching of the target attribute information with the information stored in the target buffer includes: determining a target attribute category corresponding to the target attribute information; determining the target buffer from a plurality of buffers based on the target attribute category, wherein each of the buffers corresponds to a different attribute category, and each of the buffers stores attribute information of anonymous users in the target geographic location area that is consistent with the attribute category corresponding to each buffer; If the match is successful, the geographic location information of the target anonymous user is determined based on the matched information; If the match is unsuccessful, matching the target attribute information with information stored in a target retriever, and determining the geographic location information of the target anonymous user based on the matched information, wherein the target retriever stores multiple sets of correspondences between the attribute information of anonymous users and geographic location areas; The matching of the target attribute information with the information stored in the target retriever includes: determining the target retriever from multiple retrievers based on the target attribute category, wherein each retriever corresponds to a different attribute category, and each retriever stores multiple sets of correspondences between attribute information of anonymous users consistent with the attribute category corresponding to each retriever and the geographic location.

2. The method according to claim 1, characterized in that The step of obtaining target anonymous online transaction data includes: Obtain multiple anonymous online transaction data within a preset time period; According to a preset priority setting method, priority information of each anonymous online transaction data is determined, and according to the priority information, the anonymous online transaction data with the highest priority is selected as the target anonymous online transaction data.

3. The method according to claim 2, characterized in that Before determining the priority information of each anonymous online transaction data according to the preset priority setting method, the method further includes: Obtaining attribute information of an anonymous user corresponding to each of the anonymous online transaction data, and performing filtering processing on each of the anonymous online transaction data based on the attribute information of the anonymous user corresponding to each of the anonymous online transaction data, so as to filter out anonymous online transaction data having illegal attribute information from the plurality of anonymous online transaction data; Correspondingly, determining the priority information of each anonymous online transaction data according to a preset priority setting method includes: According to the preset priority setting method, priority information of each anonymous online transaction data obtained after filtering is determined.

4. The method according to claim 1, wherein Before acquiring the target anonymous online transaction data and the business scenario information of the target anonymous online transaction data, the method further includes: Acquire multiple historical anonymous online transaction data within the target historical time period and attribute information of anonymous users corresponding to each of the historical anonymous online transaction data; For each of the historical anonymous online transaction data, matching the attribute information of the anonymous user corresponding to each of the historical anonymous online transaction data with the information in each of the search engines to obtain the historical geographical location area corresponding to each of the historical anonymous online transaction data; Collecting statistics on the historical anonymous online transaction data corresponding to each of the historical geographic location areas, and determining the historical geographic location area with the largest number of anonymous online transactions during the target historical time period as the target historical geographic location area; The attribute category corresponding to each of the retrievers and the storage information corresponding to the target historical geographical location area in each of the retrievers are obtained, and the storage information is batch loaded into a cache having the same attribute category as the retriever.

5. The method according to claim 4, characterized in that After batch loading the search information corresponding to the geographical location area in each searcher into the corresponding cache according to the attribute category, the method includes: Determining whether there is duplicate attribute information of anonymous users stored in the cache; If there is duplicated attribute information of anonymous users, the information to be retained is determined according to the time when the attribute information of each anonymous user is loaded into the cache, and the cache is updated according to the information to be retained.

6. The method according to claim 4, characterized in that The method further comprises: detecting whether a trigger instruction of the buffer is satisfied, and determining update information of the buffer if the trigger instruction is satisfied; The buffer is updated according to the update information of the buffer.

7. A device for determining geographic location information, characterized in that: The device comprises: an acquisition module, configured to acquire target anonymous online transaction data and business scenario information of the target anonymous online transaction data, and determine target attribute information of a target anonymous user corresponding to the target anonymous online transaction data based on the business scenario information; a first matching module for matching the target attribute information with information stored in a target buffer, wherein the target buffer stores attribute information corresponding to anonymous users in a geographical location where the largest number of anonymous online transactions occurred during a target historical time period; matching the target attribute information with the information stored in the target buffer comprises: determining a target attribute category corresponding to the target attribute information; determining the target buffer from a plurality of buffers based on the target attribute category, wherein each buffer corresponds to a different attribute category, and each buffer stores attribute information of anonymous users in the target geographical location that is consistent with the attribute category corresponding to each buffer; and, if a match is successful, determining the geographical location information of the target anonymous user based on the matched information; The second matching module is used to match the target attribute information with the information stored in the target retriever when the target attribute information fails to match the information stored in the target cache, and determine the geographic location information of the target anonymous user based on the matched information, wherein the target retriever stores multiple sets of correspondences between the anonymous user's attribute information and geographic location areas; matching the target attribute information with the information stored in the target retriever includes: determining the target retriever from multiple retrievers based on the target attribute category, wherein each retriever corresponds to a different attribute category, and each retriever stores multiple sets of correspondences between the anonymous user's attribute information and geographic locations that are consistent with the attribute category corresponding to each retriever.

8. The device according to claim 7, characterized in that The acquisition module includes: A data acquisition unit, configured to acquire a plurality of anonymous online transaction data within a preset time period; The priority setting unit is used to determine the priority information of each anonymous online transaction data according to a preset priority setting method, and select the anonymous online transaction data with the highest priority as the target anonymous online transaction data according to the priority information.

9. The device according to claim 8, characterized in that The device also includes a filtration module; The filtering module is configured to obtain attribute information of an anonymous user corresponding to each of the anonymous online transaction data, and perform filtering processing on each of the anonymous online transaction data based on the attribute information of the anonymous user corresponding to each of the anonymous online transaction data, so as to filter out anonymous online transaction data having illegal attribute information from the plurality of anonymous online transaction data; Correspondingly, the priority setting unit is used to determine the priority information of each anonymous online transaction data obtained after filtering according to the preset priority setting method.

10. The device according to claim 7, characterized in that The device further includes a loading module; the loading module includes: A historical data unit, configured to obtain a plurality of historical anonymous online transaction data within the target historical time period and attribute information of anonymous users corresponding to each of the historical anonymous online transaction data; a data matching unit for matching the attribute information of the anonymous user corresponding to each of the historical anonymous online transaction data with the information in each of the search engines, thereby obtaining the historical geographical location area corresponding to each of the historical anonymous online transaction data; a data statistics unit, configured to collect statistics on the historical anonymous online transaction data corresponding to each of the historical geographic location areas, and to define the historical geographic location area with the largest number of anonymous online transactions during the target historical time period as the target historical geographic location area; The data loading unit is used to obtain the attribute category corresponding to each of the retrievers and the storage information corresponding to the target historical geographical location area in each of the retrievers, and batch load the storage information into a cache with the same attribute category as the retriever.

11. The device according to claim 10, characterized in that The device also includes an update module; The update module is configured to determine whether duplicate attribute information of anonymous users is stored in the cache; if duplicate attribute information of anonymous users is stored, determine information to be retained based on the time when the attribute information of each anonymous user is loaded into the cache, and update the cache based on the information to be retained.

12. The device according to claim 10, characterized in that The device also includes a trigger module; The trigger module is configured to detect whether a trigger instruction of the cache is satisfied, and determine update information of the cache if the trigger instruction is satisfied; The buffer is updated according to the update information of the buffer.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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