CN116955709A - User data fusion processing method and system - Google Patents

User data fusion processing method and system Download PDF

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Publication number
CN116955709A
CN116955709A CN202210394641.4A CN202210394641A CN116955709A CN 116955709 A CN116955709 A CN 116955709A CN 202210394641 A CN202210394641 A CN 202210394641A CN 116955709 A CN116955709 A CN 116955709A
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Prior art keywords
user
mapping table
data
generating
log information
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CN202210394641.4A
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Chinese (zh)
Inventor
请求不公布姓名
韩腾辉
张哲铭
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Beijing Yunyou Interactive Network Technology Co ltd
Online Tuyoo Beijing Technology Co ltd
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Beijing Yunyou Interactive Network Technology Co ltd
Online Tuyoo Beijing Technology Co ltd
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Priority to CN202210394641.4A priority Critical patent/CN116955709A/en
Publication of CN116955709A publication Critical patent/CN116955709A/en
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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
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/901—Indexing; Data structures therefor; Storage structures
    • G06F16/9024—Graphs; Linked lists
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3438—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment monitoring of user actions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
    • G06F2201/80—Database-specific techniques
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The application provides a user data fusion processing method and system, a computing device and a computer readable storage medium, wherein the method comprises the steps of obtaining user log information in a plurality of systems, traversing user IDs in the user log information, and generating a point set and an edge set; and importing the point set and the edge set into a graph database, executing a connected component algorithm to obtain a result graph model, and distributing a unified identifier GUID for connected subgraphs in the result graph model to obtain an ID-Mapping table. According to the method, the processing efficiency of the associated data is greatly improved, after the ID-Mapping table is established, the behavior data of the same user in a plurality of service systems can be obtained by utilizing the Mapping relation table and the unified identifier, and the behavior portrait data of the target user is generated according to the behavior data of the target user in the plurality of service systems, so that data support is provided for the fine operation of enterprises.

Description

User data fusion processing method and system
Technical Field
The present application relates to the field of computer technologies, and in particular, to a user data fusion processing method and system, a computing device, and a computer readable storage medium.
Background
With the use of various IT systems, the behavior of users in each system is collected and recorded, and becomes a main data source for big data analysis. Because the same user in each system usually uses different account numbers or different login modes, in order to facilitate analysis of the full path behavior of the user in each system to form a user portrait, the prior art generally correlates data of the same user.
In the prior art, when processing a plurality of associated identification information, for example, when a user has a plurality of identity IDs associated with each other, complex memory traversal calculation is required, or traversal calculation is performed based on traditional database data SQL statements, so that the calculation is time-consuming and low in efficiency, for example, CN107577787a can only process 5000 pieces of data within 1 second, and the existing requirements cannot be met.
Disclosure of Invention
In view of the above, embodiments of the present application provide a user data fusion processing method and system, a computing device and a computer readable storage medium, so as to solve the technical defects existing in the prior art.
According to a first aspect of an embodiment of the present application, there is provided a user data fusion processing method, including: acquiring user log information in a multi-system, wherein the user log information comprises user IDs;
traversing the user ID in the user log information to generate a point set and an edge set;
importing the point set and the edge set into a graph database, and executing a connected component algorithm to obtain a result graph model;
distributing a unified identifier GUID to connected subgraphs in the result graph model to obtain an ID-Mapping table, and updating a history Mapping table according to the ID-Mapping table.
According to a second aspect of an embodiment of the present application, there is provided a user data fusion processing system including:
an acquisition unit configured to acquire user log information in a multisystem, the log information including a user ID;
the generating unit is used for traversing the user ID in the user log information and generating a point set and an edge set;
the computing unit is used for importing the point set and the edge set into a graph database and executing a connected component algorithm to obtain a result graph model;
and the updating unit is used for distributing a unified identifier GUID to the connected subgraphs in the result graph model to obtain an ID-Mapping table, and updating the history Mapping table according to the ID-Mapping table.
According to a third aspect of an embodiment of the present application, there is provided a method of generating a user representation, comprising:
according to the client request, acquiring a unified identification GUID of a user;
acquiring behavior data of a target user in a plurality of service systems according to the unified identification GUID and the ID-Mapping table;
user portrait data is generated according to the user behavior data and fed back.
According to a fourth aspect of an embodiment of the present application, there is provided a system for generating a representation of a user, comprising:
the query unit is used for acquiring a unified identification GUID of a user according to a client request;
the acquisition unit is used for acquiring behavior data of the target user in a plurality of service systems according to the unified identification GUID and the ID-Mapping table;
and the generating unit is used for generating user portrait data according to the user behavior data and feeding back the user portrait data.
According to a fifth aspect of embodiments of the present application, there is provided a computing device comprising a memory, a processor and computer instructions stored on the memory and executable on the processor, the processor implementing the steps of the user data fusion processing method when executing the instructions.
According to a sixth aspect of embodiments of the present application, there is provided a computer readable storage medium storing computer instructions which, when executed by a processor, implement the steps of the user data fusion processing method.
In the embodiment of the application, the user IDs of the systems and the relation between the user IDs are abstracted into points and edges of the graph, the graph calculation is used for constructing an undirected connected graph, and a unified identifier is distributed for each connected subgraph, so that an ID-Mapping table is obtained. According to the method, the processing efficiency of the associated data is greatly improved, after the ID-Mapping table is established, the behavior data of the same user in a plurality of service systems can be obtained by utilizing the Mapping relation table and the unified identifier, and the behavior portrait data of the target user is generated according to the behavior data of the target user in the plurality of service systems, so that data support is provided for the fine operation of enterprises.
Drawings
FIG. 1 is a block diagram of a computing device provided by an embodiment of the present application;
fig. 2 is a flowchart of a user data fusion processing method provided in an embodiment of the present application;
FIG. 3 is a schematic diagram of various user IDs used in the system provided by the embodiment of the present application;
FIG. 4 is a schematic diagram of a connectivity graph model for determining associated user identities provided by an embodiment of the present application;
FIG. 5 is a diagram of a user identification mapping representation intent provided by an embodiment of the present application;
FIG. 6 is a schematic diagram of a user data fusion processing system according to an embodiment of the present application;
FIG. 7 is a schematic diagram of a system for generating a representation of a user according to an embodiment of the present application;
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. The present application may be embodied in many other forms than those herein described, and those skilled in the art will readily appreciate that the present application may be similarly embodied without departing from the spirit or essential characteristics thereof, and therefore the present application is not limited to the specific embodiments disclosed below.
The terminology used in the one or more embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the application. As used in one or more embodiments of the application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present application refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that, although the terms first, second, etc. may be used in one or more embodiments of the application to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first may also be referred to as a second, and similarly, a second may also be referred to as a first, without departing from the scope of one or more embodiments of the application. The word "if" as used herein may be interpreted as "responsive to a determination" depending on the context.
In the present application, a user data fusion processing method and system, a computing device, and a computer-readable storage medium are provided, and detailed descriptions are provided in the following embodiments.
FIG. 1 illustrates a block diagram of a computing device 100, according to an embodiment of the application. The components of the computing device 100 include, but are not limited to, a memory 110 and a processor 120. Processor 120 is coupled to memory 110 via bus 130 and database 150 is used to store data.
Computing device 100 also includes access device 140, access device 140 enabling computing device 100 to communicate via one or more networks 160. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 140 may include one or more of any type of network interface, wired or wireless (e.g., a Network Interface Card (NIC)), such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the application, the above-described components of computing device 100, as well as other components not shown in FIG. 1, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device shown in FIG. 1 is for exemplary purposes only and is not intended to limit the scope of the present application. Those skilled in the art may add or replace other components as desired.
Computing device 100 may be any type of stationary or mobile computing device including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smart phone), wearable computing device (e.g., smart watch, smart glasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 100 may also be a mobile or stationary server.
Wherein the processor 120 may perform the steps of the user data fusion processing method shown in fig. 2. Fig. 2 shows a flowchart of a user data fusion processing method according to an embodiment of the present application, including steps 202 to 208.
Step 202: user log information in the multi-system is obtained, the log information including a user ID.
There are a large number of user data logs in the database of each system, which data originate from different channels or terminals, and for user data of different sources, different systems are usually recorded in different ways as required. Various devices may be used on the user side, and various front-end portals exist, and even the same user has a plurality of devices and uses various front-end portals, which results in that the number and types of possibly acquired identifiers in log data collected by the same person in different time periods are different.
For example, the user may use various devices, such as Android mobile phone, iOS mobile phone, tablet, and computer, so the ID representing the user may be one or several of mac\imei\android id\openudid\idfa\deviceid\mailbox\mobile phone number\identification card number\userid, as shown in fig. 3. And thus cannot be used as a unique identification for identifying a user based on a certain identification.
In the embodiment of the application, the user logs including the user ID in each system are collected and stored, and the user is not identified by a certain user ID.
Further, incremental user log information generated by multiple systems on the same day is obtained.
Further, in each system, the job machine is used to complete the task of collecting incremental user log information.
Step 204: traversing the user ID in the user log information to generate a point set and an edge set.
In a specific embodiment, after obtaining the user log information, a point set is generated according to the user ID in the user log information. For example, as shown in fig. 3, there are 10 users in total, different users use different user IDs, and all user IDs used by the 10 users are traversed to generate a point set (mac 01, mac02, mac03, imei01, imei02, a@a.com, b@b.com, c@c.com,15299999999, 13988888888, 13777777777).
Further, an edge set is generated according to the association relationship between the user IDs.
Whether the user IDs have an association relationship is judged, and the application is not limited to a specific rule definition method depending on business rules defined according to actual requirements, such as the occurrence of the user IDs in the same record, the occurrence of the user IDs in association events, the occurrence time intervals and the like. As shown in fig. 3, for the connection relationship existing between different user IDs belonging to the same user log record, the following set is generated:
Edge1(1,imei02)
Edge2(1,mac01)
Edge3(1,15299999999)
Edge4(2,mac01)
Edge5(2,imei01)
Edge6(3,imei01)
Edge7(3,a@a.com)
Edge8(7,15299999999)
Edge8(6,13988888888)
Edge9(6,b@b.com)
Edge10(5,b@b.com)
Edge11(5,mac02)
Edge12(4,mac03)
Edge13(9,mac03)
Edge14(9,c@c.com)
Edge15(8,c@c.com)
Edge16(8,13777777777)
Edge17(10,13777777777)
further, incremental user log information collected daily is stored in a distributed file system (HDFS), and the point set and edge set generating function is completed by using a big data analysis cluster.
Step 206: and importing the point set and the edge set into a graph database, and executing a connected component algorithm to obtain a result graph model.
In a specific embodiment, the graph database includes historical user data.
After the point set and the edge set generated in the step 204 are imported into the graph database, the graph database respectively combines the history point set and the edge set with the imported point set and the imported edge set to obtain a new point set and a new edge set.
Further, the connected component calculation is performed on the new point set and the edge set, so as to obtain a result graph model, as shown in fig. 4.
Further, the graph database is a GES database.
In step 206, the graph calculation method of the connected components is adopted, so that the traversal query work of the cascade data is avoided, and the processing efficiency of the associated data is greatly improved; the maximum grouping set can be quickly identified through graph calculation and the association path between IDs can be carried out, and 1 hundred million pieces of data can be calculated and completed in 1 minute.
Step 208: distributing a unified identifier GUID to connected subgraphs in the result graph model to obtain an ID-Mapping table, and updating a history Mapping table according to the ID-Mapping table.
As shown in fig. 4, in the result graph, there are a plurality of connected sub-graphs, and these sub-graphs enclosed by the dotted lines represent virtually the same user, for example userids 1, 2, 3, 7 are virtually the same user. Thus, each connected subgraph is assigned a unified identity GUID.
Further, a Mapping relationship is established between the user IDs in all the connected subgraphs in the result graph model and the GUIDs to which the user IDs belong, so as to obtain an ID-Mapping table, as shown in FIG. 5.
Further, the newly generated ID-Mapping table and the existing ID-Mapping table are combined to obtain a final ID-Mapping table.
When merging, a new GUID is used in ID-Mapping for the newly added connected subgraphs, and for the case that the existing connected subgraphs are newly added with user IDs, an old GUID is still used and a new Mapping relation is added under the GUID.
In the above embodiment of the present application, the data islands in each system are opened through the ID-Mapping table, and users of different functional systems are connected in series with a unified ID. After the data island is broken, users and products can be known more comprehensively and completely, and a data base is tamped for refined operation. The core technology of the ID-Mapping table is to abstract the user IDs of the systems and the relation between the user IDs into points and edges of the graph, and the graph calculation algorithm is used for easily judging the same object, so that an undirected connected graph is constructed, and the Mapping table is generated. After the ID-Mapping table is established, the behavior data of the same user in a plurality of service systems can be obtained by utilizing the Mapping relation table and the unified identifier, and the behavior portrait data of the target user is generated according to the behavior data of the target user in the plurality of service systems, so that data support is provided for the fine operation of enterprises.
In another embodiment, a method of generating a user representation is provided, comprising steps 302-306:
302: according to the client request, acquiring a unified identification GUID of a user;
the query system receives a data acquisition request sent by a client, the request including a user ID, the user ID being any one of the plurality of user IDs. And the query system queries in the ID-Mapping table according to the user ID to obtain a unified identifier of the target user and a plurality of user identifiers corresponding to the unified identifier.
The client request is triggered by the user clicking on the user interface of the client, for example, when the user logs in to the client application or clicks into a certain functional module, and the client request can be implemented by a person skilled in the art according to actual requirements, which is not particularly limited herein.
304: and acquiring behavior data of the target user in a plurality of service systems according to the unified identification GUID and the ID-Mapping table.
In the embodiment, according to the obtained unified identification GUID of the user, all user IDs with Mapping relation with the GUID and the system to which the user IDs belong are inquired in an ID-Mapping table. In the log record of each system, the behavior data of the user is obtained according to the user ID query, and the behavior data includes, but is not limited to, clicking, browsing, participating in activities, etc. of the target user in the system, which is not particularly limited herein.
306: user portrait data is generated according to the user behavior data and fed back.
Specifically, after the behavior data of the user in a plurality of service systems is obtained, the travel portrait data of the target user is generated according to the behavior data of the target user in the service systems, and is fed back to the target system.
In one possible implementation, behavior data of the target user in a plurality of business systems are integrated in time sequence to form portrait data of the target user.
In another possible implementation, the portrait data of the target user is formed according to the behavior types of the target user in a plurality of business systems.
In another possible implementation manner, portrait data of the target user is formed according to attribute values corresponding to behavior types of the target user in a plurality of service systems.
In this embodiment, the query system may respond to the request of the client to obtain the unified identifier of the target user, obtain the behavior data of the target user in multiple service systems by using the ID-Mapping table and the unified identifier of the target user, generate the trip portrait data of the target user according to the behavior data of the target user in the multiple service systems, and send the trip portrait data of the target user to the terminal device, and may use the unified identifier to correlate the behaviors of the user in each service system, thereby improving the accuracy of user portrait description and providing data support for the refined operation of the enterprise.
Corresponding to the above method embodiment, the present application further provides an embodiment of a user data fusion processing system, as shown in fig. 6, where the system 600 includes:
an acquisition unit configured to acquire user log information in a multisystem, the log information including a user ID;
the generating unit is used for traversing the user ID in the user log information and generating a point set and an edge set;
the computing unit is used for importing the point set and the edge set into a graph database and executing a connected component algorithm to obtain a result graph;
and the updating unit is used for distributing a unified identifier for the connected subgraphs in the result graph model and updating the mapping table.
Corresponding to the above method embodiment, the present application further provides an embodiment of a user portrait generating system, as shown in fig. 7, where the system 700 includes:
the query unit is used for acquiring a unified identification GUID of a user according to a client request;
the acquisition unit is used for acquiring behavior data of the target user in a plurality of service systems according to the unified identification GUID and the ID-Mapping table;
and the generating unit is used for generating user portrait data according to the user behavior data and feeding back the user portrait data.
The foregoing is a schematic solution of a user data fusion processing system and a user image generating system of the present embodiment. It should be noted that, the technical solution of the system belongs to the same concept as the technical solution of a user data fusion processing method and a user portrait generating method, and details of the technical solution of the system, which are not described in detail, can be referred to the description of the technical solution of the user data fusion processing method and the user portrait generating method.
In one embodiment, the present application further provides a computing device, including a memory, a processor, and computer instructions stored in the memory and capable of running on the processor, where the processor implements the steps of a user data fusion processing method and a user portrait generating method when executing the instructions.
The foregoing is a schematic illustration of a computing device of this embodiment. It should be noted that, the technical solution of the computing device belongs to the same concept as the technical solution of the above-mentioned user data fusion processing method and the technical solution of the method for generating the user portrait, and details of the technical solution of the computing device which are not described in detail can be referred to the description of the technical solution of the above-mentioned user data fusion processing method and the technical solution of the method for generating the user portrait.
An embodiment of the present application also provides a computer-readable storage medium storing computer instructions that when executed by a processor implement the steps of a user data fusion processing method and a method of generating a user representation as described above.
The above is an exemplary version of a computer-readable storage medium of the present embodiment. It should be noted that, the technical solution of the storage medium and the technical solutions of the above-mentioned user data fusion processing method and the user portrait generating method belong to the same concept, and details of the technical solution of the storage medium which are not described in detail can be referred to the description of the technical solutions of the above-mentioned user data fusion processing method and the user portrait generating method.
The foregoing describes certain embodiments of the present application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The computer instructions include computer program code that may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
It should be noted that, for the sake of simplicity of description, the foregoing method embodiments are all expressed as a series of combinations of actions, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily all required for the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.
The preferred embodiments of the application disclosed above are intended only to assist in the explanation of the application. Alternative embodiments are not intended to be exhaustive or to limit the application to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the application and the practical application, to thereby enable others skilled in the art to best understand and utilize the application. The application is limited only by the claims and the full scope and equivalents thereof.

Claims (10)

1. A user data fusion processing method, comprising:
acquiring user log information in a plurality of systems, wherein the user log information comprises user IDs;
traversing the user ID in the user log information to generate a point set and an edge set;
importing the point set and the edge set into a graph database, and executing a connected component algorithm to obtain a result graph model;
distributing a unified identifier GUID to connected subgraphs in the result graph model to obtain an ID-Mapping table, and updating a history Mapping table according to the ID-Mapping table.
2. The method of claim 1, wherein the obtaining user log information in the plurality of systems obtains incremental user log information generated on a day of the plurality of systems.
3. The method of claim 1, wherein the generating the set of points and the set of edges comprises:
generating a point set according to all the user IDs;
and generating an edge set according to the association relation between the user IDs.
4. The method of claim 3, wherein the updating the history Mapping table according to the ID-Mapping table comprises:
using a new GUID in an ID-Mapping table for the newly added connected subgraph;
for the case of an existing connected subgraph but a newly added user ID, the old GUID is still used, and a new user ID mapping relationship is added under the GUID.
5. The method of claim 1, wherein the user ID includes, but is not limited to:
one or more of mac value, imei value, androidId, openUDID, idfa value, deviceId, mailbox, mobile phone number, identification card number, QQ number and userid of the device.
6. A method of generating a user representation in accordance with the method of claim 1, comprising:
according to the client request, acquiring a unified identification GUID of a user;
acquiring behavior data of a target user in a plurality of service systems according to the unified identification GUID and the ID-Mapping table;
and generating user portrait data according to the behavior data and feeding back the user portrait data.
7. A user data fusion processing system, comprising:
an acquisition unit configured to acquire user log information in a multisystem, the log information including a user ID;
the generating unit is used for traversing the user ID in the user log information and generating a point set and an edge set;
the computing unit is used for importing the point set and the edge set into a graph database and executing a connected component algorithm to obtain a result graph model;
and the updating unit is used for distributing a unified identifier GUID to the connected subgraphs in the result graph model to obtain an ID-Mapping table, and updating the history Mapping table according to the ID-Mapping table.
8. A system for generating a user representation in accordance with the method of claim 1, comprising:
the query unit is used for acquiring a unified identification GUID of a user according to a client request;
the acquisition unit is used for acquiring behavior data of the target user in a plurality of service systems according to the unified identification GUID and the ID-Mapping table;
and the generating unit is used for generating user portrait data according to the user behavior data and feeding back the user portrait data.
9. A computing device comprising a memory, a processor, and computer instructions stored on the memory and executable on the processor, wherein the processor, when executing the instructions, implements the steps of the method of any of claims 1-6.
10. A computer readable storage medium storing computer instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 6.
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CN117271850A (en) * 2023-11-17 2023-12-22 上海光潾网络科技有限公司 User data matching method, platform, equipment and medium based on client data platform

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117271850A (en) * 2023-11-17 2023-12-22 上海光潾网络科技有限公司 User data matching method, platform, equipment and medium based on client data platform
CN117271850B (en) * 2023-11-17 2024-01-30 上海光潾网络科技有限公司 User data matching method, platform, equipment and medium based on client data platform

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