WO2020233093A1 - 关联图谱生成方法、装置、计算机设备和存储介质 - Google Patents

关联图谱生成方法、装置、计算机设备和存储介质 Download PDF

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WO2020233093A1
WO2020233093A1 PCT/CN2019/122866 CN2019122866W WO2020233093A1 WO 2020233093 A1 WO2020233093 A1 WO 2020233093A1 CN 2019122866 W CN2019122866 W CN 2019122866W WO 2020233093 A1 WO2020233093 A1 WO 2020233093A1
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target
association
current
record
information
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PCT/CN2019/122866
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English (en)
French (fr)
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田恬
徐志成
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深圳壹账通智能科技有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/288—Entity relationship models

Definitions

  • This application relates to a method, device, computer equipment and storage medium for generating an association map.
  • the data information is manually constructed associative map.
  • the internal generation logic of the traditional correlation map is relatively complicated, and it takes a lot of time to construct the data each time. Sometimes after the correlation map generation logic is fine-tuned, the previously constructed data will be invalid. The correlation map generator needs to reorganize according to the adjusted logic The test data is time-consuming, reduces work efficiency, and cannot generate correlation maps quickly and accurately.
  • a method, device, computer device and storage medium for generating an association map are provided, which can quickly and accurately generate an association map.
  • a method for generating an association map includes:
  • association relationship corresponding to the target user ID cannot be obtained from the association relationship set, and the association factor corresponding to the association relationship cannot be found, then an association is generated based on each target association record in the record pool Atlas.
  • An associated map generating device including:
  • the current identification acquiring module is used to acquire the association relationship set and data information sent by the terminal, and acquire the current user identification from the data information;
  • An association factor obtaining module configured to obtain the current association relationship corresponding to the current user identifier from the association relationship set, and find the current association factor corresponding to the current association relationship;
  • the target identification acquiring module is configured to acquire the target correlation factor corresponding to the current correlation factor from the data information, and search for the target user identification corresponding to the target correlation factor;
  • An associated record generating module configured to associate the current user identifier and the target user identifier through the current association factor or the target association factor, generate a target association record, and add the target association record to a record pool;
  • the association graph generation module is configured to, if the association relationship corresponding to the target user identifier cannot be obtained from the association relationship set, and the association factor corresponding to the association relationship cannot be found, then according to the record pool The associated records of each target generate an associated map.
  • a computer device including a memory and one or more processors, the memory stores computer readable instructions, when the computer readable instructions are executed by the processor, the one or more processors execute The following steps:
  • association relationship corresponding to the target user ID cannot be obtained from the association relationship set, and the association factor corresponding to the association relationship cannot be found, then an association is generated based on each target association record in the record pool Atlas.
  • One or more non-volatile storage media storing computer-readable instructions.
  • the computer-readable instructions When executed by one or more processors, the one or more processors perform the following steps:
  • association relationship corresponding to the target user ID cannot be obtained from the association relationship set, and the association factor corresponding to the association relationship cannot be found, then an association is generated based on each target association record in the record pool Atlas.
  • Fig. 1 is an application environment diagram of a method for generating an association map according to one or more embodiments.
  • Fig. 2 is a method flowchart of a method for generating an association map according to one or more embodiments.
  • Fig. 3 is a flowchart of a method for generating a target association record in a method for generating an association map according to one or more embodiments.
  • Fig. 4 is a flowchart of a method for determining a target correlation factor in a method for generating a correlation map according to one or more embodiments.
  • Fig. 5 is a block diagram of a method and apparatus for generating an association graph according to one or more embodiments.
  • Figure 6 is a block diagram of a computer device according to one or more embodiments.
  • the association graph generation method provided in the embodiments of the present application can be applied to the application environment shown in FIG. 1.
  • the server 120 obtains the association relationship set and data information sent by the terminal 110, and the server 120 obtains the current user ID from the data information. Obtain the current association relationship corresponding to the current user ID from the association relationship set, the server 120 searches for the current association factor corresponding to the current association relationship, obtains the target association factor corresponding to the current association factor from the data information, and the server 120 searches for the association with the target The target user identification corresponding to the factor, the server 120 associates the current user identification and the target user identification through the current correlation factor or the target correlation factor to generate a target correlation record. The server 120 adds the target correlation record to the record pool. The association relationship corresponding to the target user identifier cannot be obtained, and the association factor corresponding to the association relationship cannot be found, the association map is generated according to each target association record in the record pool.
  • the method specifically includes the following steps:
  • Step 202 Obtain the association relationship set and data information sent by the terminal, and obtain the current user identifier from the data information.
  • the association relationship collection is a collection including multiple association relationships.
  • Association relationships in the association relationship set include, but are not limited to, call relationship association, address book relationship association, SMS relationship association, mobile phone number association, home address association, work unit association, device fingerprint association, account association and bank account association.
  • Data information includes user identification, correlation factor, associated user information, and associated user detailed information.
  • the current user ID is a user ID randomly extracted by the server from the data information, and the server uses the randomly extracted user ID as the current user ID.
  • the user ID may be ID card information.
  • the correlation factor is an intermediary that associates the current user ID with the target user ID
  • the associated user information is information associated with the user ID.
  • Associated user information includes but is not limited to work unit, geographic location, home address, device fingerprint, ID number, bank account number, mailbox, WIFI, IP, company phone, base station and account number.
  • the associated user detailed information is the detailed data information corresponding to the associated user information. For example, when the associated user information is "mailbox", the associated user detailed information is the specific address of the mailbox.
  • the server can create a blank configuration file, the server sends the blank configuration file to the terminal, and the terminal defines the data information and association relationship set in the configuration file.
  • the terminal defines each user identification and association in the configuration file. The user information and the detailed information of the associated user, as well as the association factor and association relationship corresponding to each user identifier are defined, and the terminal sends the defined association relationship set and data information to the server.
  • Step 204 Obtain the current association relationship corresponding to the current user identifier from the association relationship set, and search for the current association factor corresponding to the current association relationship.
  • the association relationship corresponding to each user identifier is information predefined by the terminal and stored in the association relationship set. It can be understood that the current association relationship is a predefined association relationship corresponding to the current user identifier.
  • the server searches the data information for the current association factor corresponding to the current association relationship, where the current association factor is a factor associated with the current association relationship for associating the current user identifier with the target user identifier. For example, when the current user identifier randomly extracted by the server from the data information is A, and the current association relationship predefined by the terminal to A is "work unit association", the current association factor is searched according to A's current association relationship "work unit association" "employer".
  • Step 206 Obtain the target correlation factor corresponding to the current correlation factor from the data information, and search for the target user identifier corresponding to the target correlation factor.
  • the target correlation factor is a factor that has the same data information as the current correlation factor. For example, when the current correlation factor of A is "work unit", the server searches the data information for the terminal's pre-defined data information through the current correlation factor "work unit" A has the target correlation factor of the same work unit.
  • the server searches for the target user identification corresponding to the target correlation factor, and associates the current user identification and the target user identification with the current correlation factor or the target correlation factor to generate the target correlation record.
  • Step 208 Associate the current user identifier and the target user identifier through the current correlation factor or the target correlation factor to generate a target correlation record, and add the target correlation record to the record pool.
  • the server associates the current user identifier and the target user identifier through the current correlation factor or the target correlation factor to generate a target correlation record.
  • the target correlation record is a completed one-time correlation relationship.
  • the server adds each constructed target association record to the record pool, so that the server generates a complete association map according to each target association record in the record pool.
  • Step 210 If the association relationship corresponding to the target user identifier cannot be obtained from the association relationship set, and the association factor corresponding to the association relationship cannot be found, then an association map is generated according to each target association record in the record pool.
  • the server If the server cannot obtain the association relationship corresponding to the target user identifier from the association relationship set, and cannot find the association factor corresponding to the association relationship, it generates an association map according to each target association record in the record pool. That is, the server uses the target user identifier as the current user identifier to return to the step of obtaining the current association relationship corresponding to the current user identifier from the association relationship set. When the server completes a target association record, the server will continue to construct the next target association record until all the user IDs with predefined association relationships in the data information generate the corresponding target association records, according to the target association records in the record pool Record and generate a correlation map.
  • association relationship corresponding to the target user ID cannot be obtained from the association relationship set, and the association factor corresponding to the association relationship cannot be found, that is, the user ID in the data information whose association relationship is predefined by the terminal will generate corresponding
  • an association map is generated based on each target associated record in the record pool.
  • the relationship map is a diagram describing the relationship between individuals and individuals, and the display of the relationship map includes, but is not limited to, tree-shaped, circular, and list-shaped.
  • the terminal sends a script to the server.
  • the script is an extension of the batch file and is a program saved in plain text.
  • the terminal defines an array of 12 association factors in the script. Assuming that a 5-degree association relationship will be constructed, 5 values are defined in each array.
  • the server receives the script generated by the terminal. When the user is identified as ID card information, the server will A data A is randomly selected from the ID card array, and the association relationship and association factor associated with the ID card in the data information are checked at the same time, and a value is read from the association factor array respectively, and the server will complete the first association relationship. Then randomly select a value B from the remaining four values in the ID card array, and check the correlation between A and B, then the value of the correlation factor of B takes the same value as the correlation factor of A.
  • the correlation factor "mobile phone number” of B is the same as the value of the correlation factor "mobile phone number” of A, and the remaining 11 correlation factors in A are related to B The values of the 11 correlation factors are different.
  • a second-degree correlation is generated, that is, a target correlation record is generated.
  • the server randomly selects a value C from the remaining three values of the ID card array, and at the same time checks the correlation between B and C, the value of the correlation factor of C takes the same value as the correlation factor of B, for example, when When the association relationship between B and C defined by the terminal is home address association, then the association factor "home address" of C and the association factor "home address” of B take the same value, and the remaining 11 association factors in B are the same as those in C The values of the 11 association factors are different.
  • the three-degree association relationship is constructed, that is, a target association record is generated again. It is understandable that the construction principles of the fourth-degree association and the fifth-degree association are the same as the above methods.
  • the server can write the data of the constructed correlation map into a file in CSV or TXT format, which is convenient for real-time calling.
  • the server obtains the association relationship set and data information sent by the terminal.
  • the current user ID and the target user ID can be quickly associated, and then randomly extracted
  • the local current user ID obtains its corresponding current association relationship.
  • the server can obtain the corresponding current association factor according to the current association relationship to further find the target association factor, and obtain the target user ID according to the target association factor, which can accurately identify the current user
  • the identification and the target user identification are associated through the current correlation factor or target correlation factor.
  • the server will loop the steps of the correlation until the terminal defines the user identification of the correlation relationship.
  • the correlation map is quickly generated according to the target correlation records in the record pool. .
  • the method further includes the following steps:
  • Step 302 Obtain current associated user information corresponding to the current user identifier, and generate a first associated record based on the current user identifier and the current associated user information.
  • the current associated user information is the remaining associated factors in addition to the current associated factors.
  • the current associated user information is the remaining 11 correlation factors, namely geographic location, home address, device fingerprint, ID number, bank account number, email address, WIFI, IP, company phone, base station and account.
  • the server associates the current associated user information with the current user identifier, and generates a first associated record.
  • the first associated record includes the current user identifier and the current associated user information.
  • Step 304 Obtain target associated user information corresponding to the target user identifier, and generate a second associated record according to the target user identifier and the target associated user information.
  • the target related user information is the remaining related factors except the current one.
  • the correlation factor is "bank account number”
  • the target associated user information is the remaining 11 correlation factors, namely work unit, geographic location, home address, device fingerprint, ID number, mailbox, WIFI, IP, company phone, base station and account
  • the second association record includes target user identification and target associated user information.
  • Step 306 Associate the first association record with the second association record according to the current association factor or the target association factor to generate a target association record.
  • the server associates the first association record with the second association record according to the current association factor or the target association factor, the server will obtain the current user identifier in the first association record and the target user identifier in the second association record, and then according to The current correlation factor or the target correlation factor associates the current user ID with the target user ID to generate a target correlation record.
  • the server obtains the first associated record and the second associated record, and then associates the user identification in the first associated record with the second associated record, and can display the user identification in detail in the generated target associated record. Relevant information makes the association map more specific and clear when displayed.
  • the method further includes: obtaining each associated user information from the association map, and obtaining the associated user detailed information corresponding to the associated user information; associating the hyperlink of the associated user information to the associated user detailed information, when When the jump operation corresponding to the associated user information is triggered, jump from the associated user information to the associated user detailed information according to the hyperlink.
  • Associated user information is information associated with user identification, and associated user detailed information is specific data of associated user information.
  • Associated user information includes but is not limited to work unit, geographic location, home address, device fingerprint, ID number, bank account number, mailbox, WIFI, IP, company phone, base station and account number. For example, when the associated user information is "work unit”, the detailed information of the associated user is the detailed address of the "work unit”, and when the associated user information is "bank account”, the detailed information of the associated user is the specific address of the "bank account”. account number.
  • the server associates the hyperlink of the associated user information with the associated user detailed information, that is, when the server receives a terminal triggering instruction on the hyperlink, it will jump from the associated user information to the associated user detailed information.
  • the terminal can activate these links by clicking the linked associated user information, and set an underline or display in different colors under the linked associated user information to distinguish.
  • the server obtains each associated user information from the associated map, and then obtains the associated user detailed information corresponding to the associated user information, and associates the hyperlink of the associated user information to the associated user detailed information, and the associated map displays
  • the association relationship between each data information due to the large amount of data information, the association graph is not clear enough when all the data is displayed at the same time, so set the hyperlink jump relationship in each associated user information, for example, when the terminal triggers the work When working as a unit, the detailed address of the work unit will be displayed.
  • the detailed address is the detailed information of the associated user, which can achieve the purpose of viewing the specific data of each associated user information in detail.
  • the method further includes the following steps:
  • Step 402 Obtain the detailed information of the correlation factor corresponding to the current correlation factor.
  • the correlation factor detailed information is the specific information of the current correlation factor. For example, when the server determines that the current correlation factor is the "bank account number”, it will obtain the correlation factor detailed information corresponding to the "bank account number", that is, the "bank account number" According to the specific account information, the server searches the data information for the target user ID with the same account information, so as to realize the association between the current user ID and the target user ID.
  • Step 404 Traverse the data information according to the correlation factor refinement information, and obtain the target correlation factor refinement information that is the same as the correlation factor refinement information from the data information.
  • the server when the server obtains the current user identification, it will read the current association relationship that is predefined by the terminal and corresponding to the current user identification. The server determines the current association factor according to the current association relationship, because the current association factor and the target association factor have the same data Therefore, the target user identification can be further determined through the current correlation factor.
  • Step 406 Determine the target correlation factor corresponding to the refined information of the target correlation factor.
  • the server determines the corresponding target correlation factor according to the detailed information of the target correlation factor. For example, when the detailed information of the target correlation factor is "XXX Co., Ltd.”, the server will automatically identify the target correlation factor as the "work unit" and determine the target correlation The factor can further determine the target user ID, which is used to generate target association records.
  • the server obtains the correlation factor refinement information corresponding to the current correlation factor, and then traverses the data information according to the correlation factor refinement information, and obtains the target correlation factor refinement information that is the same as the correlation factor refinement information from the data information, Through the refined information of the target association factor, the target association factor can be further determined, and the target user identifier can be accurately found according to the determined target association factor, so as to further generate the target association record and improve the accuracy of the target association record generation.
  • the method further includes: sending the association relationship rule and the data information rule to the corresponding terminal; instructing the terminal to input the association relationship set according to the association relationship rule, and instructing the terminal to input data information according to the data information rule.
  • association relationship rule is used to instruct the terminal to input the association relationship correctly
  • data information rule user instructs the terminal to input data information correctly. Due to the huge amount of data information, in order to better generate an intuitive and clear association map, it is necessary to instruct the terminal to input the association relationship set and data information according to certain rules.
  • the server sends the association relationship rule and the data information rule to the corresponding terminal.
  • the association relationship rule and the data information rule can instruct the terminal to input the correct association relationship set and data information, improve the efficiency of the association map generation, and make the association map The display is more intuitive and clear.
  • a schematic diagram of an apparatus for generating an association graph includes:
  • the current identity obtaining module 502 is used to obtain the association relationship set and data information sent by the terminal, and obtain the current user identity from the data information;
  • the correlation factor acquisition module 504 is configured to acquire the current correlation relationship corresponding to the current user identifier from the correlation relationship set, and find the current correlation factor corresponding to the current correlation relationship;
  • the target identification obtaining module 506 is configured to obtain the target correlation factor corresponding to the current correlation factor from the data information, and find the target user identification corresponding to the target correlation factor;
  • the associated record generation module 508 is used to associate the current user ID and the target user ID through the current or target association factor to generate a target association record, and add the target association record to the record pool;
  • the association map generation module 510 if the association relationship corresponding to the target user identifier cannot be obtained from the association relationship set, and the association factor corresponding to the association relationship cannot be found, the association map is generated according to each target association record in the record pool.
  • the associated record generation module includes: a first record generation module, configured to obtain current associated user information corresponding to the current user identifier, and generate a first associated record based on the current user identifier and the current associated user information; second The record generation module is used to obtain the target associated user information corresponding to the target user identifier, and generate a second association record according to the target user identifier and the target associated user information; the record association module is used to compare the first association record according to the current association factor or the target association factor The associated record and the second associated record are associated to generate a target associated record.
  • the correlation map generation module includes: a detailed information acquisition module, which is used to acquire information about each associated user from the correlation map, and obtain detailed information about the associated user corresponding to the associated user information; and a link jump module for The hyperlink of the associated user information is associated with the associated user detailed information, and when the jump operation corresponding to the associated user information is triggered, jump from the associated user information to the associated user detailed information according to the hyperlink.
  • the target correlation factor determination module includes: acquiring correlation factor refinement information corresponding to the current correlation factor; traversing the data information according to the correlation factor refinement information, and obtaining from the data information the same as the correlation factor refinement information Target correlation factor detailed information; determine the target correlation factor corresponding to the target correlation factor detailed information.
  • the information acquisition module includes: sending the association relationship rule and the data information rule to the corresponding terminal; instructing the terminal to input the association relationship set according to the association relationship rule, and instructing the terminal to input data information according to the data information rule.
  • Each module in the above-mentioned association map generation device can be implemented in whole or in part by software, hardware, and a combination thereof.
  • the foregoing modules may be embedded in the form of hardware or independent of the processor in the computer device, or may be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the foregoing modules.
  • the processor can be a central processing unit (CPU), a microprocessor, a single-chip microcomputer, etc.
  • the above-mentioned association map generation device may be implemented in a form of computer readable instructions.
  • a computer device is provided.
  • the computer device may be a server or a terminal.
  • the computer device When the computer device is a terminal, its internal structure diagram can be as shown in Figure 6.
  • the computer equipment includes a processor, a memory, and a network interface connected through a system bus.
  • the processor of the computer device is used to provide calculation 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 computer readable instructions.
  • the internal memory provides an environment for the operation of the operating system and computer-readable instructions in the non-volatile storage medium.
  • the network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer-readable instructions are executed by the processor, an association map generation method is realized.
  • FIG. 6 is only a block diagram of 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 Including more or fewer parts than shown in the figure, or combining some parts, or having a different arrangement of parts.
  • a computer device includes a memory and one or more processors.
  • the memory stores computer-readable instructions.
  • the steps of the correlation graph generation method provided in any embodiment of the present application are realized.
  • One or more non-volatile storage media storing computer-readable instructions.
  • the computer-readable instructions are executed by one or more processors, the one or more processors realize the association provided in any of the embodiments of the present application Steps of the map generation method.
  • a person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing relevant hardware through computer-readable instructions, which can be stored in a non-volatile computer.
  • computer-readable instructions when the computer-readable instructions are executed, they may include the processes of the above-mentioned method embodiments.
  • the storage medium can be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), and the like.

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Abstract

一种关联图谱生成方法包括：从数据信息中获取当前用户标识；查找与当前关联关系对应的当前关联因子；从数据信息中获取与当前关联因子对应的目标关联因子，查找与目标关联因子对应的目标用户标识；将当前用户标识和目标用户标识通过当前关联因子或目标关联因子进行关联，生成目标关联记录，将目标关联记录加入记录池中；若从关联关系集合中获取不到与目标用户标识对应的关联关系，且查找不到与关联关系对应的关联因子，则根据记录池中的各个目标关联记录生成关联图谱。

Description

关联图谱生成方法、装置、计算机设备和存储介质
相关申请的交叉引用
本申请要求于2019年05月20日提交中国专利局，申请号为201910418819.2，申请名称为“关联图谱生成方法、装置、计算机设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及一种关联图谱生成方法、装置、计算机设备和存储介质。
背景技术
随着计算机技术领域的高速发展，人们每天都在面对大量的数据信息，当需要向业务方演示关联网络相关的功能时，都需要花费大量时间去收集满足业务方需求的数据信息，并根据数据信息手动进行构造关联图谱。
传统地关联图谱内部生成逻辑相对复杂，每次构造数据都需要耗费大量时间，有时关联图谱生成逻辑微调过后，就会导致之前构造的数据失效，关联图谱生成方又需要根据调整后的逻辑重新梳理测试数据，及其耗费时间，降低工作效率，不能快捷并且准确地生成关联图谱。
发明内容
根据本申请公开的各种实施例，提供一种关联图谱生成方法、装置、计算机设备和存储介质，能够快捷并且准确地生成关联图谱。
一种关联图谱生成方法，包括：
获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识；
从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查 找与所述当前关联关系对应的当前关联因子；
从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；及
若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
一种关联图谱生成装置，包括：
当前标识获取模块，用于获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识；
关联因子获取模块，用于从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查找与所述当前关联关系对应的当前关联因子；
目标标识获取模块，用于从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
关联记录生成模块，用于将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；及
关联图谱生成模块，用于若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
一种计算机设备，包括存储器和一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述处理器执行时，使得所述一个或多个处理器执行以下步骤：
获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用 户标识；
从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查找与所述当前关联关系对应的当前关联因子；
从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；及
若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行以下步骤：
获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识；
从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查找与所述当前关联关系对应的当前关联因子；
从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；及
若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的 其它特征和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。
图1为根据一个或多个实施例中关联图谱生成方法的应用环境图。
图2为根据一个或多个实施例中关联图谱生成方法的方法流程图。
图3为根据一个或多个实施例中关联图谱生成方法中生成目标关联记录的方法流程图。
图4为根据一个或多个实施例中关联图谱生成方法中确定目标关联因子的方法流程图。
图5为根据一个或多个实施例中关联图谱生成方法装置的框图。
图6为根据一个或多个实施例中计算机设备的框图。
具体实施方式
为了使本申请的技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
本申请实施例中所提供的关联图谱生成方法可以应用于如图1所示的应用环境中，服务器120获取终端110发送的关联关系集合和数据信息，服务器120从数据信息中获取当前用户标识，从关联关系集合中获取与当前用户标识对应的当前关联关系，服务器120查找与当前关联关系对应的当前关联因子，从数据信息中获取与当前关联因子对应的目标关联因子，服务器120查找与目标关联因子对应的目标用户标识，服务器120将当前用户标识和目标用户标识通过当前关联因子或目标关联因子进行关联，生成目标关联记录，服务器120将目 标关联记录加入记录池中，若从关联关系集合中获取不到与目标用户标识对应的关联关系，且查找不到与关联关系对应的关联因子，则根据记录池中的各个目标关联记录生成关联图谱。
下述实施方式以关联图谱生成方法应用于图1的服务器为例进行说明，但需要说明的是，实际应用中该方法并不仅限应用于上述服务器。
如图2所示，在其中一个实施例中的关联图谱生成方法的流程图，该方法具体包括以下步骤：
步骤202，获取终端发送的关联关系集合和数据信息，从数据信息中获取当前用户标识。
关联关系集合是包括多种关联关系的集合。关联关系集合中的关联关系包括但不限于通话关系关联、通讯录关系关联、短信关系关联、手机号关联、家庭地址关联、工作单位关联、设备指纹关联、账号关联和银行账号关联。数据信息包括用户标识、关联因子、关联用户信息和关联用户细化信息。当前用户标识为服务器从数据信息中随机抽取的用户标识，服务器将随机抽取的用户标识作为当前用户标识，特别地，用户标识可为身份证信息。
具体地，关联因子是当前用户标识与目标用户标识进行关联的中介，关联用户信息是与用户标识相关联的信息。关联用户信息包括但不限于工作单位、地理位置、家庭地址、设备指纹、证件号、银行账号、邮箱、WIFI、IP、公司电话、基站和账号。关联用户细化信息为关联用户信息所对应的详细的数据信息，例如，当关联用户信息为“邮箱”时，关联用户细化信息即邮箱的具体地址。
在其中一个实施例中，服务器可创建一个空白配置文件，服务器将空白配置文件发送至终端，终端将在配置文件中定义数据信息和关联关系集合，例如终端在配置文件中定义各个用户标识、关联用户信息和关联用户细化信息，以及定义各个用户标识所对应的关联因子以及关联关系，终端再将定义好的关联关系集合和数据信息发送至服务器。
步骤204，从关联关系集合中获取与当前用户标识对应的当前关联关系，查 找与当前关联关系对应的当前关联因子。
各个用户标识对应的关联关系是由终端预先定义并存储至关联关系集合中的信息。可以理解的是，当前关联关系是预先定义的与当前用户标识对应的关联关系。
具体地，服务器从数据信息中查找与当前关联关系对应的当前关联因子，当前关联因子是与当前关联关系所关联的用于当前用户标识和目标用户标识进行关联的因子。例如，当服务器从数据信息中随机抽取出的当前用户标识为A，终端对A预先定义的当前关联关系为“工作单位关联”，则根据A的当前关联关系“工作单位关联”查找当前关联因子“工作单位”。
步骤206，从数据信息中获取与当前关联因子对应的目标关联因子，查找与目标关联因子对应的目标用户标识。
目标关联因子是与当前关联因子具有相同的数据信息的因子，例如，当A的当前关联因子为“工作单位”时，服务器通过当前关联因子“工作单位”在数据信息中查找终端预先定义的与A具有相同工作单位的目标关联因子。
具体地，服务器通过目标关联因子查找与其对应的目标用户标识，将当前用户标识和目标用户标识通过当前关联因子或目标关联因子进行关联，生成目标关联记录。
步骤208，将当前用户标识和目标用户标识通过当前关联因子或目标关联因子进行关联，生成目标关联记录，将目标关联记录加入记录池中。
具体地，服务器将当前用户标识和目标用户标识通过当前关联因子或目标关联因子进行关联，生成目标关联记录，可以理解的是，目标关联记录是构建完成的一度关联关系。服务器将构建好的每一条目标关联记录加入记录池中，以用于服务器根据记录池中的各个目标关联记录生成完整的关联图谱。
步骤210，若从关联关系集合中获取不到与目标用户标识对应的关联关系，且查找不到与关联关系对应的关联因子，则根据记录池中的各个目标关联记录生成关联图谱。
服务器若从关联关系集合中获取不到与目标用户标识对应的关联关系，且 查找不到与关联关系对应的关联因子，则根据记录池中的各个目标关联记录生成关联图谱。即，服务器将目标用户标识作为当前用户标识，以用于返回从关联关系集合中获取与当前用户标识对应的当前关联关系的步骤。当服务器构建完成一条目标关联记录时，服务器将继续构建下一目标关联记录，直至数据信息中所有被预先定义关联关系的用户标识都生成相应的目标关联记录时，根据记录池中的各个目标关联记录生成关联图谱。
具体地，若从关联关系集合中获取不到与目标用户标识对应的关联关系，且查找不到与关联关系对应的关联因子，即数据信息中被终端预先定义关联关系的用户标识都生成相应的目标关联记录时，根据记录池中的各个目标关联记录生成关联图谱。可以理解的是，关系图谱是描述个体及个体之间关系的图，关联图谱的显示包括但不限于树状形、圆形和列表形。
在其中一个实施例中，终端将编写一个脚本发送至服务器，脚本是批处理文件的延伸，是一种纯文本保存的程序。终端在脚本中定义12个关联因子的数组，假设将构建5度关联关系，则每个数组中定义5个数值，服务器接收终端生成的脚本，当用户标识为身份证信息时，服务器将从身份证数组中随机抽取一个数据A，同时查看数据信息中与身份证相关联的关联关系和关联因子，分别从关联因子数组中读取一个值，服务器将构建完成一度关联关系。再从身份证数组中剩下的四个值随机抽取一个值B，同时查看A与B的关联关系，则B的关联因子的值取与A的关联因子相同的值。
例如，当终端定义的A与B的关联关系为手机号关联，那么B的关联因子“手机号”则与A的关联因子“手机号”的值相同，A中剩余的11种关联因子与B中的11种关联因子的取值不同，此时生成二度关联关系，即生成一条目标关联记录。
进一步地，服务器再从身份证数组剩下的三个值中随机抽取一个值C，同时查看B与C的关联关系，C的关联因子的值取与B的关联因子相同的值，例如，当终端定义的B与C的关联关系为家庭地址关联时，那么C的关联因子“家庭地址”与B的关联因子“家庭地址”取相同的值，B中剩余的11种关联因子与 C中的11种关联因子的取值不同，此时构建完成三度关联关系，即再次生成一条目标关联记录。可以理解的是，四度关联关系和五度关联关系构造原理与上述方法同理。特别地，服务器可将构造完成的关联图谱的数据写入到CSV或TXT格式的文件中，方便实时调用。
本实施例中，服务器获取终端发送的关联关系集合和数据信息，通过获取终端预先定义好的关联关系和相关的数据信息，能够将当前用户标识和目标用户标识进行快捷地关联，再通过随机抽取地当前用户标识获取与其对应的当前关联关系，服务器根据当前关联关系能够获取对应的当前关联因子，以用于进一步查找到目标关联因子，根据目标关联因子获取目标用户标识，能够准确地将当前用户标识和目标用户标识通过当前关联因子或目标关联因子进行关联，服务器将循环关联的步骤，直至终端定义关联关系的各个用户标识都关联完毕，根据记录池中的各个目标关联记录快捷地生成关联图谱。
在其中一个实施例中，如图3所示，该方法还包括以下步骤：
步骤302，获取与当前用户标识对应的当前关联用户信息，根据当前用户标识和当前关联用户信息生成第一关联记录。
，当前关联用户信息是除当前关联因子外剩余的关联因子。当有12种关联因子时，例如，当关联因子为“工作单位”时，当前关联用户信息为剩余的11种关联因子，即地理位置、家庭地址、设备指纹、证件号、银行账号、邮箱、WIFI、IP、公司电话、基站和账号。服务器将当前关联用户信息关联至当前用户标识，生成第一关联记录，第一关联记录包括当前用户标识以及当前关联用户信息。
步骤304，获取与目标用户标识对应的目标关联用户信息，根据目标用户标识和目标关联用户信息生成第二关联记录。
，目标关联用户信息是除当前关联因子外剩余的关联因子。当有12种关联因子时，例如，当关联因子为“银行账号”时，目标关联用户信息为剩余的11种关联因子，即工作单位、地理位置、家庭地址、设备指纹、证件号、邮箱、WIFI、IP、公司电话、基站和账号，第二关联记录包括目标用户标识以及目标 关联用户信息。
步骤306，根据当前关联因子或目标关联因子将第一关联记录和第二关联记录进行关联，生成目标关联记录。
具体地，服务器根据当前关联因子或目标关联因子将第一关联记录和第二关联记录进行关联，服务器将获取第一关联记录中的当前用户标识和第二关联记录中的目标用户标识，再根据当前关联因子或目标关联因子将当前用户标识和目标用户标识进行关联，生成目标关联记录。
本实施例中，服务器通过获取第一关联记录和第二关联记录，再将第一关联记录和第二关联记录中的用户标识进行关联，能够在生成的目标关联记录中详细的展示与用户标识相关的信息，使得关联图谱在展示时更为具体和清晰。
在其中一个实施例中，该方法还包括：从关联图谱中获取各个关联用户信息，获取关联用户信息对应的关联用户细化信息；将关联用户信息的超链接关联至关联用户细化信息，当关联用户信息对应的跳转操作被触发时，根据超链接从关联用户信息跳转至关联用户细化信息。
关联用户信息为与用户标识相关联的信息，关联用户细化信息是关联用户信息的具体数据。关联用户信息包括但不限于工作单位、地理位置、家庭地址、设备指纹、证件号、银行账号、邮箱、WIFI、IP、公司电话、基站和账号。例如，当关联用户信息为“工作单位”时，关联用户细化信息是“工作单位”的详细地址，当关联用户信息为“银行账号”时，关联用户细化信息为“银行账号”的具体账号。
具体地，服务器将关联用户信息的超链接关联至关联用户细化信息，即当服务器接收终端对超链接的触发指令时，将从关联用户信息跳转至关联用户细化信息。终端可以通过点击被链接的关联用户信息来激活这些链接，在被链接的关联用户信息下设置下划线或者以不同的颜色显示来进行区分。
本实施例中，服务器从关联图谱中获取各个关联用户信息，再获取关联用户信息对应的关联用户细化信息，并将关联用户信息的超链接关联至关联用户细化信息，关联图谱显示的是各个数据信息之间的关联关系，由于数据信息的 数据量较大，同时显示所有数据时该关联图谱不够清晰明了，因此在各个关联用户信息中设置超链接跳转关系，例如，当终端触发工作单位时，将展示工作单位的详细地址，该详细地址为关联用户细化信息，能够实现详细地查看各个关联用户信息的具体数据的目的。
在其中一个实施例中，如图4所示，该方法还包括以下步骤：
步骤402，获取与当前关联因子对应的关联因子细化信息。
具体地，关联因子细化信息是当前关联因子的具体信息，例如，当服务器确定当前关联因子为“银行账号”时，将获取“银行账号”对应的关联因子细化信息，即“银行账号”的具体账号信息，服务器根据具体账号信息在数据信息中进行查找具有相同账号信息的目标用户标识，以此实现当前用户标识与目标用户标识的关联。
步骤404，根据关联因子细化信息遍历数据信息，从数据信息中获取与关联因子细化信息相同的目标关联因子细化信息。
具体地，当服务器获取当前用户标识时，将读取终端预先定义的与当前用户标识对应的当前关联关系，服务器根据当前关联关系确定当前关联因子，由于当前关联因子与目标关联因子具有相同的数据信息，因此通过当前关联因子能够进一步确定目标用户标识。
步骤406，确定与目标关联因子细化信息对应的目标关联因子。
服务器根据目标关联因子细化信息确定对应的目标关联因子，例如，当目标关联因子细化信息为“XXX有限公司”时，服务器将自动识别该目标关联因子为“工作单位”，通过确定目标关联因子能够进一步确定目标用户标识，目标用户标识用于生成目标关联记录。
本实施例中，服务器获取与当前关联因子对应的关联因子细化信息，再根据关联因子细化信息遍历数据信息，从数据信息中获取与关联因子细化信息相同的目标关联因子细化信息，通过目标关联因子细化信息能够进一步确定目标关联因子，能够准确地根据确定的目标关联因子查找到目标用户标识，以用于进一步生成目标关联记录，提高目标关联记录生成的准确性。
在其中一个实施例中，该方法还包括：将关联关系规则和数据信息规则发送至对应的终端；指示终端根据关联关系规则输入关联关系集合，指示终端根据数据信息规则输入数据信息。
具体地，关联关系规则用于指示终端正确地输入关联关系，数据信息规则用户指示终端正确地输入数据信息。由于数据信息量巨大，为更好地生成直观且清晰的关联图谱，因此需要指示终端按照一定规则输入关联关系集合和数据信息。
本实施例中，服务器将关联关系规则和数据信息规则发送至对应的终端，关联关系规则和数据信息规则能够指示终端输入正确地关联关系集合和数据信息，提高关联图谱生成的效率，使得关联图谱的显示更为直观和清晰。
如图5所示，在其中一个实施例中的关联图谱生成装置的示意图，该装置包括：
当前标识获取模块502，用于获取终端发送的关联关系集合和数据信息，从数据信息中获取当前用户标识；
关联因子获取模块504，用于从关联关系集合中获取与当前用户标识对应的当前关联关系，查找与当前关联关系对应的当前关联因子；
目标标识获取模块506，用于从数据信息中获取与当前关联因子对应的目标关联因子，查找与目标关联因子对应的目标用户标识；
关联记录生成模块508，用于将当前用户标识和目标用户标识通过当前关联因子或目标关联因子进行关联，生成目标关联记录，将目标关联记录加入记录池中；
关联图谱生成模块510，若从关联关系集合中获取不到与目标用户标识对应的关联关系，且查找不到与关联关系对应的关联因子，则根据记录池中的各个目标关联记录生成关联图谱。
在其中一个实施例中，关联记录生成模块包括：第一记录生成模块，用于获取与当前用户标识对应的当前关联用户信息，根据当前用户标识和当前关联用户信息生成第一关联记录；第二记录生成模块，用于获取与目标用户标识对 应的目标关联用户信息，根据目标用户标识和目标关联用户信息生成第二关联记录；记录关联模块，用于根据当前关联因子或目标关联因子将第一关联记录和第二关联记录进行关联，生成目标关联记录。
在其中一个实施例中，关联图谱生成模块包括：细化信息获取模块，用于从关联图谱中获取各个关联用户信息，获取关联用户信息对应的关联用户细化信息；链接跳转模块，用于将关联用户信息的超链接关联至关联用户细化信息，当关联用户信息对应的跳转操作被触发时，根据超链接从关联用户信息跳转至关联用户细化信息。
在其中一个实施例中，目标关联因子确定模块包括：获取与当前关联因子对应的关联因子细化信息；根据关联因子细化信息遍历数据信息，从数据信息中获取与关联因子细化信息相同的目标关联因子细化信息；确定与目标关联因子细化信息对应的目标关联因子。
在其中一个实施例中，信息获取模块包括：将关联关系规则和数据信息规则发送至对应的终端；指示终端根据关联关系规则输入关联关系集合，指示终端根据数据信息规则输入数据信息。
关于关联图谱生成装置的具体限定可以参见上文中对于关联图谱生成方法的限定，在此不再赘述。上述关联图谱生成装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。该处理器可以为中央处理单元(CPU)、微处理器、单片机等。上述关联图谱生成装置可以实现为一种计算机可读指令的形式。
在一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，也可以是终端。当该计算机设备为终端时，其内部结构图可以如图6所示。该计算机设备包括通过系统总线连接的处理器、存储器和网络接口。该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作系统和计算机可读指令。 该内存储器为非易失性存储介质中的操作系统和计算机可读指令的运行提供环境。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机可读指令被处理器执行时以实现一种关联图谱生成方法。本领域技术人员可以理解，图6中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
一种计算机设备，包括存储器和一个或多个处理器，存储器中存储有计算机可读指令，计算机可读指令被处理器执行时实现本申请任意一个实施例中提供的关联图谱生成方法的步骤。
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器实现本申请任意一个实施例中提供的关联图谱生成方法的步骤。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，所述的计算机可读指令可存储于一非易失性计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-OnlyMemory，ROM)等。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (18)

  1. 一种关联图谱生成方法，包括：
    获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识；
    从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查找与所述当前关联关系对应的当前关联因子；
    从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
    将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；及
    若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
  2. 根据权利要求1所述的方法，其特征在于，所述将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中，包括：
    获取与当前用户标识对应的当前关联用户信息，根据所述当前用户标识和当前关联用户信息生成第一关联记录；
    获取与目标用户标识对应的目标关联用户信息，根据所述目标用户标识和目标关联用户信息生成第二关联记录；及
    根据所述当前关联因子或所述目标关联因子将所述第一关联记录和所述第二关联记录进行关联，生成目标关联记录。
  3. 根据权利要求2所述的方法，其特征在于，所述若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联 关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱之后，还包括：
    从所述关联图谱中获取各个关联用户信息，获取所述关联用户信息对应的关联用户细化信息；
    将所述关联用户信息的超链接关联至所述关联用户细化信息，当所述关联用户信息对应的跳转操作被触发时，根据所述超链接从关联用户信息跳转至所述关联用户细化信息。
  4. 根据权利要求1所述的方法，其特征在于，所述从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识，包括：
    获取与所述当前关联因子对应的关联因子细化信息；
    根据关联因子细化信息遍历所述数据信息，从所述数据信息中获取与所述关联因子细化信息相同的目标关联因子细化信息；及
    确定与所述目标关联因子细化信息对应的目标关联因子。
  5. 根据权利要求1所述的方法，其特征在于，所述获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识之前，还包括：
    将关联关系规则和数据信息规则发送至对应的终端；
    指示所述终端根据所述关联关系规则输入关联关系集合，指示所述终端根据所述数据信息规则输入数据信息。
  6. 一种关联图谱生成装置，包括：
    当前标识获取模块，用于获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识；
    关联因子获取模块，用于从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查找与所述当前关联关系对应的当前关联因子；
    目标标识获取模块，用于从所述数据信息中获取与所述当前关联因子对 应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
    关联记录生成模块，用于将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；
    关联图谱生成模块，用于若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
  7. 根据权利要求6所述的装置，其特征在于，所述关联记录生成模块包括：
    第一记录生成模块，用于获取与当前用户标识对应的当前关联用户信息，根据所述当前用户标识和当前关联用户信息生成第一关联记录；
    第二记录生成模块，用于获取与目标用户标识对应的目标关联用户信息，根据所述目标用户标识和目标关联用户信息生成第二关联记录；
    记录关联模块，用于根据所述当前关联因子或所述目标关联因子将所述第一关联记录和所述第二关联记录进行关联，生成目标关联记录。
  8. 根据权利要求6所述的装置，其特征在于，所述关联图谱生成模块包括：
    细化信息获取模块，用于从所述关联图谱中获取各个关联用户信息，获取所述关联用户信息对应的关联用户细化信息；
    链接跳转模块，用于将所述关联用户信息的超链接关联至所述关联用户细化信息，当所述关联用户信息对应的跳转操作被触发时，根据所述超链接从关联用户信息跳转至所述关联用户细化信息。
  9. 一种计算机设备，包括存储器及一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识；
    从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查找与所述当前关联关系对应的当前关联因子；
    从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
    将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；及
    若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
  10. 根据权利要求9所述的计算机设备，其特征在于，所述将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中，包括：
    获取与当前用户标识对应的当前关联用户信息，根据所述当前用户标识和当前关联用户信息生成第一关联记录；
    获取与目标用户标识对应的目标关联用户信息，根据所述目标用户标识和目标关联用户信息生成第二关联记录；及
    根据所述当前关联因子或所述目标关联因子将所述第一关联记录和所述第二关联记录进行关联，生成目标关联记录。
  11. 根据权利要求10所述的计算机设备，其特征在于，所述若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱之后，还包括：
    从所述关联图谱中获取各个关联用户信息，获取所述关联用户信息对应的关联用户细化信息；
    将所述关联用户信息的超链接关联至所述关联用户细化信息，当所述关联用户信息对应的跳转操作被触发时，根据所述超链接从关联用户信息跳转至所述关联用户细化信息。
  12. 根据权利要求9所述的计算机设备，其特征在于，所述从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识，包括：
    获取与所述当前关联因子对应的关联因子细化信息；
    根据关联因子细化信息遍历所述数据信息，从所述数据信息中获取与所述关联因子细化信息相同的目标关联因子细化信息；及
    确定与所述目标关联因子细化信息对应的目标关联因子。
  13. 根据权利要求9所述的计算机设备，其特征在于，所述获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识之前，还包括：
    将关联关系规则和数据信息规则发送至对应的终端；
    指示所述终端根据所述关联关系规则输入关联关系集合，指示所述终端根据所述数据信息规则输入数据信息。
  14. 一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识；
    从所述关联关系集合中获取与所述当前用户标识对应的当前关联关系，查找与所述当前关联关系对应的当前关联因子；
    从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识；
    将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中；及
    若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱。
  15. 根据权利要求14所述的存储介质，其特征在于，所述将所述当前用户标识和所述目标用户标识通过所述当前关联因子或所述目标关联因子进行关联，生成目标关联记录，将所述目标关联记录加入记录池中，包括：
    获取与当前用户标识对应的当前关联用户信息，根据所述当前用户标识和当前关联用户信息生成第一关联记录；
    获取与目标用户标识对应的目标关联用户信息，根据所述目标用户标识和目标关联用户信息生成第二关联记录；及
    根据所述当前关联因子或所述目标关联因子将所述第一关联记录和所述第二关联记录进行关联，生成目标关联记录。
  16. 根据权利要求15所述的存储介质，其特征在于，所述若从所述关联关系集合中获取不到与所述目标用户标识对应的关联关系，且查找不到与所述关联关系对应的关联因子，则根据所述记录池中的各个目标关联记录生成关联图谱之后，还包括：
    从所述关联图谱中获取各个关联用户信息，获取所述关联用户信息对应的关联用户细化信息；
    将所述关联用户信息的超链接关联至所述关联用户细化信息，当所述关联用户信息对应的跳转操作被触发时，根据所述超链接从关联用户信息跳转 至所述关联用户细化信息。
  17. 根据权利要求14所述的存储介质，其特征在于，所述从所述数据信息中获取与所述当前关联因子对应的目标关联因子，查找与所述目标关联因子对应的目标用户标识，包括：
    获取与所述当前关联因子对应的关联因子细化信息；
    根据关联因子细化信息遍历所述数据信息，从所述数据信息中获取与所述关联因子细化信息相同的目标关联因子细化信息；及
    确定与所述目标关联因子细化信息对应的目标关联因子。
  18. 根据权利要求14所述的存储介质，其特征在于，所述获取终端发送的关联关系集合和数据信息，从所述数据信息中获取当前用户标识之前，还包括：
    将关联关系规则和数据信息规则发送至对应的终端；
    指示所述终端根据所述关联关系规则输入关联关系集合，指示所述终端根据所述数据信息规则输入数据信息。
PCT/CN2019/122866 2019-05-20 2019-12-04 关联图谱生成方法、装置、计算机设备和存储介质 WO2020233093A1 (zh)

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