CN115795426A

CN115795426A - Data processing method, apparatus, device, medium, and program product

Info

Publication number: CN115795426A
Application number: CN202211559968.9A
Authority: CN
Inventors: 涂晴宇; 张宇鸿; 石雪; 陈继轩
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2022-12-06
Filing date: 2022-12-06
Publication date: 2023-03-14

Abstract

The present disclosure provides a data processing method, apparatus, device, medium, and program product, which relate to the field of big data technology, in particular to the field of data processing technology, and can be applied to the field of financial technology. The method comprises the following steps: determining identity data of a user to be detected in response to login data of a first terminal of the user; comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result; and under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship, determining user prompt information according to the identity data of the user to be detected, wherein the target association relationship comprises at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

Description

Data processing method, apparatus, device, medium, and program product

Technical Field

The present disclosure relates to the field of big data technologies, and in particular, to a data processing method, apparatus, device, medium, and program product.

Background

In some application scenarios, there is a need to prompt relevant staff to enter a target scenario for a target user, such as a store, so that the relevant staff can better provide services to the target user.

With the development of computer technology and big data technology, relevant data in the application scenarios can be generated and processed by relevant electronic devices. How to efficiently process related data so as to prompt a worker that a target user enters a target scene becomes a technical problem to be solved urgently.

Disclosure of Invention

In view of the above, the present disclosure provides a data processing method applied to a first server side, a data processing apparatus applied to the first server side, a data processing method applied to a second server side, a data processing apparatus applied to the second server side, a data processing method applied to a third server side, a data processing apparatus applied to the third server side, a device, a medium, and a program product.

According to an aspect of the present disclosure, there is provided a data processing method applied to a first server side, including: the method comprises the steps of responding to login data of a first terminal of a user, and determining identity data of the user to be detected; comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result; and under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship, determining user prompt information according to the identity data of the user to be detected, wherein the target association relationship comprises at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

According to another aspect of the embodiments of the present disclosure, there is provided a data processing method applied to a second server, including: receiving user data of a first terminal or a second terminal through a first server, wherein the second terminal is used for receiving user prompt information; determining an inventory user knowledge graph according to user data, and determining a target user identity data set according to the inventory user knowledge graph and target user standard data, wherein the target user identity data set comprises identity data of a target user, and the identity data of the target user is used for detecting the identity data of a user to be detected to obtain a first comparison result.

According to another aspect of the embodiments of the present disclosure, there is provided a data processing method applied to a third server, including: receiving user data of a first terminal or a second terminal; determining an inventory user knowledge graph according to user data; determining a target user identity data set according to the stock user knowledge graph and the target user standard data; the method comprises the steps of responding to login information of a first terminal of a user, and determining identity data of the user to be detected; comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result, wherein the target user identity data set comprises the identity data of the target user; and under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship, determining user prompt information according to the identity data of the user to be detected, wherein the target association relationship comprises at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

According to another aspect of the embodiments of the present disclosure, there is provided a data processing apparatus applied to a first server side, including: the device comprises an identity data determining module of a user to be detected, a first comparison result determining module and a user prompt information determining module. The identity data determining module of the user to be detected is used for responding to login data of a first terminal of the user and determining the identity data of the user to be detected; the first comparison result determining module is used for comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result; the user prompt information determination module is configured to determine user prompt information according to the identity data of the user to be detected when the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship, where the target association relationship includes at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

According to another aspect of the embodiments of the present disclosure, there is provided a data processing apparatus applied to a second server side, including: the system comprises a user data determining module, an inventory user knowledge graph determining module and a target user identity data set determining module. The user data determining module is used for receiving the user data of the first terminal or the second terminal through the first server; and the stock user knowledge graph determining module is used for determining the stock user knowledge graph according to the user data. And the target user identity data set determining module is used for determining a target user identity data set according to the stock user knowledge graph and the target user standard data, wherein the target user identity data set comprises the identity data of the target user, and the identity data of the target user is used for detecting the identity data of the user to be detected to obtain a first comparison result.

According to another aspect of the embodiments of the present disclosure, there is provided a data processing apparatus applied to a third server side, including: the receiving module is used for receiving user data of the first terminal or the second terminal; the first determining module is used for determining an inventory user knowledge graph according to user data; the second determining module is used for determining a target user identity data set according to the stock user knowledge graph and the target user standard data; the third determining module is used for responding to the login information of the first terminal aiming at the user and determining the identity data of the user to be detected; the comparison module is used for comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result, wherein the target user identity data set comprises the identity data of the target user; a fourth determining module, configured to determine, according to the identity data of the user to be detected, user prompt information when the first comparison result indicates that the identity data of the user to be detected and the identity data of the target user have a target association relationship, where the target association relationship includes at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

Another aspect of the present disclosure provides an electronic device including: one or more processors; a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the data processing method described above.

Another aspect of the present disclosure also provides a computer-readable storage medium having stored thereon executable instructions, which when executed by a processor, cause the processor to perform the above-mentioned data processing method.

Another aspect of the present disclosure also provides a computer program product comprising a computer program stored on at least one of a readable storage medium and an electronic device, the computer program, when executed by a processor, implementing the data processing method described above.

Drawings

The foregoing and other objects, features and advantages of the disclosure will be apparent from the following description of embodiments of the disclosure, taken in conjunction with the accompanying drawings of which:

fig. 1 schematically shows application scenario diagrams of a data processing method applied to a first server side, a data processing method applied to a second server side, a data processing method applied to a third server side, an apparatus, a device, a medium, and a program product according to an embodiment of the present disclosure;

fig. 2 schematically shows a flow chart of a data processing method applied to a first server side according to an embodiment of the present disclosure;

FIG. 3 schematically shows a flow chart for obtaining a first comparison result according to an embodiment of the present disclosure;

fig. 4 schematically shows a flow chart of a data processing method applied to a first server side according to yet another embodiment of the present disclosure;

fig. 5 schematically shows a flow chart of a data processing method applied to the second server side according to an embodiment of the present disclosure;

fig. 6 schematically shows a flow chart of a data processing method applied to a second server side according to another embodiment of the present disclosure;

FIG. 7 schematically shows a schematic diagram of a data processing method according to an embodiment of the present disclosure;

FIG. 8 schematically shows a schematic diagram of a data processing method according to another embodiment of the present disclosure;

FIG. 9 schematically shows a schematic diagram of a data processing method according to a further embodiment of the present disclosure;

fig. 10 schematically shows a schematic diagram of data interaction at a first server side with a second server side according to a data processing method of a further embodiment of the present disclosure;

fig. 11 is a schematic diagram illustrating a data interaction between a first server and a first terminal and a second terminal according to a data processing method according to another embodiment of the disclosure;

fig. 12 is a block diagram schematically showing a structure of a data processing apparatus applied to a first server side according to an embodiment of the present disclosure;

fig. 13 is a block diagram schematically showing a configuration of a data processing apparatus applied to a second server side according to an embodiment of the present disclosure;

fig. 14 is a block diagram schematically showing the configuration of a data processing apparatus applied to a third server side according to an embodiment of the present disclosure; and

fig. 15 schematically shows a block diagram of an electronic device adapted to implement a data processing method applied to a first server side, a data processing method applied to a second server side, and a data processing method applied to a third server side according to an embodiment of the present disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.

In those instances where a convention analogous to "at least one of A, B, and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B, and C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.).

With the development of computer technology and big data technology, relevant data in the application scenarios can be generated and processed by relevant electronic devices.

Taking a bank application scenario as an example, a user can arrive at a network point, perform identity verification and obtain a queued number by swiping an identity card on a number calling machine, and can transact business on an intelligent machine supporting business transaction or a manual window by swiping a bank card, and some workers such as a hall manager and the like can inquire related information of the user by holding electronic equipment such as a tablet personal computer and the like, and assist the user in transacting business and the like.

In a banking application scenario, there is a need to prompt a target user to a store, for example, to a lobby manager so that relevant staff can better provide services to the target user. At present, no effective systematic target user arrival reminding mechanism exists, and the main problem is that before a user handles actual business and swipes an identity card or provides a bank card, related staff of a bank outlet cannot determine whether a user arriving at a store is a target user.

Some embodiments, for example, manually maintain target user lists including target user data by related staff of bank outlets, where the manually maintained target user lists are not shared and unified among the various banks, which may cause different banks to provide distinct services for the same user, affect the experience of the target user, and may cause a problem of untimely update.

In other embodiments, a staff member such as a hall manager inputs information such as a bank card number of a user through a device such as a tablet computer, and the system queries related data of the user to identify whether the user is a target user. In a time period with a large number of users arriving at the store, such as on weekends, around holidays, and the like, the above-mentioned one-to-one query of the user-related data cannot be executed, and it may not be possible to query each user to determine whether the user is a target user.

In some embodiments, only the target user is reminded to go to the store himself, ignoring users who have an affinity with the target user.

It should be noted that the data processing method applied to the first server side, the data processing method applied to the second server side, the data processing method applied to the third server side, and the corresponding apparatus determined in the embodiments of the present disclosure may be used in the financial field, and may also be used in any field other than the financial field.

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure, application and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations, necessary confidentiality measures are taken, and the customs of the public order is not violated.

In the technical scheme of the disclosure, before the personal information of the user is obtained or collected, the authorization or the consent of the user is obtained.

Fig. 1 schematically shows application scenario diagrams of a data processing method applied to a first server side, a data processing method applied to a second server side, a data processing method applied to a third server side, an apparatus, a device, a medium, and a program product according to an embodiment of the present disclosure.

As shown in fig. 1, the application scenario 100 according to this embodiment may include a first server 105, a second server 106, a third server 103, a first terminal 101, a second terminal 102, and a network 104. The network 104 is used to provide a medium for communication links between the first server 105, the second server 106, the third server 103, the first terminal 101 and the second terminal 102. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

A user may use the first terminal 101, the second terminal 102 to interact with the first server 105, the second server 106 via the network 104 to receive or send messages, etc.

The first terminal 101 may be a terminal device for a user, and may be various electronic devices having a display screen and supporting user operations and web browsing, for example, a machine for handling banking services, such as a number calling machine or a machine capable of handling related services.

The second terminal 102 may be a terminal device for a staff, and may be various electronic devices having a display screen and supporting operations of the staff and web browsing, taking the bank transaction as an example, and the second terminal may be a tablet computer operated by the staff, for example.

The first server 105, the second server 106, and the third server 103 may be servers providing various services, such as a background management server (for example only) providing support for websites browsed by users or workers using the first terminal 101 and the second terminal 102. The backend management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a web page, information, or data obtained or generated according to the user request) to the first terminal 105 and the second terminal 106.

It should be noted that the data processing method applied to the first server side provided by the embodiment of the present disclosure may be generally executed by the first server 105. Accordingly, the data processing apparatus applied to the first server provided by the embodiment of the present disclosure may be generally disposed in the first server 105. The data processing method applied to the second server end provided by the embodiment of the present disclosure may be generally executed by the second server 106. Accordingly, the data processing apparatus applied to the second server provided by the embodiment of the present disclosure may be generally disposed in the second server 106. The data processing method applied to the third server provided by the embodiment of the present disclosure may be generally performed by the third server 103. The data processing method applied to the first server side, the data processing method applied to the second server side, and the data processing method applied to the third server provided by the embodiment of the present disclosure may also be executed by a server or a server cluster that is different from the server and can communicate with the first terminal 101, the second terminal 102, and/or the server. Accordingly, the data processing device applied to the first server, the data processing device applied to the second server, and the data processing device applied to the third server provided by the embodiments of the present disclosure may also be disposed in a server or a server cluster that is different from the server and is capable of communicating with the first terminal 101, the second terminal 102, and/or the server.

It should be understood that the number of first terminals, second terminals, networks, first servers, second servers, and third servers in fig. 1 are merely illustrative. There may be any number of first terminals, second terminals, networks, first servers, second servers, and third servers, as desired for implementation.

A data processing method applied to a first server side, a data processing method applied to a second server side, and a data processing method applied to a third server side of the disclosed embodiment will be described in detail below with reference to fig. 2 to 11 based on the scenario described in fig. 1.

Fig. 2 schematically shows a flowchart of a data processing method applied to a first server side according to an embodiment of the present disclosure.

As shown in fig. 2, the data processing method of this embodiment includes operations S210 to S230, and the data processing method applied to the first server side may be performed by the first server.

In operation S210, identity data of a user to be detected is determined in response to login data for a first terminal of the user.

Still taking a banking application scenario as an example, the first terminal may be, for example, a number calling machine or an intelligent machine supporting service handling, where the number calling machine may be understood as a machine that obtains a serial number of the service handling by a way that a user verifies an identity through a certificate such as a bank card or an identity card.

It can be understood that the user can log in the first terminal by verifying the identity, and the first terminal can identify the identity of the user determined by the related certificate, that is, the identity data of the user to be detected.

In operation S220, the identity data of the user to be detected is compared with the identity data of the target user to obtain a first comparison result.

The target user may be understood as a user who desires attention. For example, the target users may include: users handling a plurality of services, users handling a number of services at a bank, and the like.

The first comparison result can represent the identity relationship between the user to be detected and the target user.

In operation S230, in a case that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have the target association relationship, determining user prompt information according to the identity data of the user to be detected.

The target association may include, for example, at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes. And when the types of the target association relations are the same, the user to be detected and the target user are the same user, and the user to be detected is the target user. The relationship of the blood relationship attribute may be understood as a relationship of the target differentiated according to the blood relationship, and the relationship of the social attribute may be understood as a relationship of the target differentiated according to the identity of the social attribute.

Exemplarily, the blood relationship attribute association management may include, for example: immediate relatives, non-immediate relatives. The social attribute association relationship may include, for example: colleagues, teachers and students, partners, and the like.

Still taking the banking application scenario as an example, other users who are closely related to the target user should also be concerned. The data processing method applied to the first server side of the embodiment of the disclosure takes other users having a target association relationship with the target user as users for reminding workers besides the target user, so that the workers can provide services for other users having close relationship with the target user.

Illustratively, the user prompt information may be sent to a second terminal for the staff member, for example.

According to the data processing method applied to the first server side, the identity relationship between the user to be detected and the target user can be represented by the first comparison result obtained by comparing the identity data of the user to be detected with the identity data of the target user, the user related to the target user and needing attention can be expanded on the basis of the target user under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have the target association relationship, and the determined user prompt information can be sent to the second terminal of the worker according to the identity data of the user to be detected, so that the worker can obtain the user to be detected with the target association relationship with the identity data of the target user through the second terminal, and better service is provided for the user.

Fig. 3 schematically shows a flowchart for obtaining a first comparison result in a data processing method applied to a first server according to another embodiment of the present disclosure.

As shown in fig. 3, for example, the following embodiments may be implemented to compare the identity data of the user to be detected with the identity data of the target user, so as to obtain a specific example of the first comparison result.

In operation S321, first map-associated data related to the identity data of the target user or second map-associated data related to the identity data of the user to be detected is determined according to the inventory user knowledge map.

Still taking the bank application scenario as an example, when a certain user opens a bank account, the user data of the user is saved, and when a subsequent user transacts related services, the user data of the user is synchronously updated, and the user data can be understood as the related data of the user. For example, the database will have stored therein the inventory of users, and user data for each user of the inventory. An inventory user knowledgegraph may be understood as user data of an inventory of users characterized by a form of a knowledgegraph, e.g., an inventory user knowledgegraph may characterize each user's name, address, transacted business, and identity associations between users, etc.

Illustratively, the identity association relationship between the users in the inventory user knowledge graph can be obtained by remark information filled by the users through the first terminal or remark information added by staff through the second terminal.

The first map associated data may be understood as data related to the target user in the inventory user knowledge map, such as name, address, transaction service of the target user and identity association relationship between the target user and other users. The second map associated data may be understood as data related to the user to be detected in the inventory user knowledge map, such as a name, an address, a transaction service of the user to be detected, and an identity association relationship between the target user to be detected and other users.

In operation S322, the identity data of the user to be detected is compared with the first map-associated data or the identity data of the target user is compared with the second map-associated data, so as to obtain a first comparison result.

According to the data processing method applied to the first server side, the inventory user knowledge graph can cover all users and user data of each user, the first graph associated data or the second graph associated data determined by the inventory user knowledge graph are more complete, and therefore the obtained first comparison result is more accurate.

Under the bank application scene, the organization structure of the bank is as follows: head office-branch-individual network points, where the user will transact business. When the staff at each site maintains the target users, the following situations may occur: one user is maintained as a target user by the network point A, and is not maintained as the target user at the network point B.

According to the data processing method applied to the first server side, the first comparison results obtained through comparison of the stock user knowledge maps are uniform in all the network points.

Illustratively, operations S321 to S322 may be performed between operations S210 and S230, for example.

Fig. 4 schematically shows a flowchart of a data processing method applied to a first server according to another embodiment of the present disclosure.

As shown in fig. 4, the data processing method 300 applied to the first server side according to still another embodiment of the present disclosure may include, for example, operation S350.

In operation S350, in a case that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have the target association relationship, the user recommendation information is determined according to recommendation information index data related to the identity data of the user to be detected.

The recommendation information indicator data comprises at least one of: user portrait data, user business data and user identity association relation data.

User representation data may be understood as data that may be used to characterize the natural attributes, characteristics of a user. For example, the user representation data may include user personality data.

User traffic data may be understood as data related to a traffic scenario. Taking a banking application scenario as an example, the user service data may include, for example: financial product data handled by the user, asset data of the user, and the like.

It can be understood that, under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have the target association relationship, related personnel can be prompted to pay attention to the user to be detected through the user prompt information.

Still taking the bank as an example, the recommendation information such as financial products can be accurately determined according to the recommendation information index data of the user portrait data, the user business data and the user identity association relation data.

Illustratively, the operation S350 may be performed after the above-described operation S220, or after the operation S230, or after the operation S240, for example.

Fig. 4 further schematically shows a data processing method 300 applied to the first server side according to yet another embodiment of the present disclosure.

The target user identity data set includes identity data of the target user. As shown in fig. 4, the data processing method 300 applied to the first server according to another embodiment of the present disclosure may further include: operation S360-operation S370.

In operation S360, when the identity data of the user to be detected corresponds to the new user, a second comparison result is determined according to the identity data of the user to be detected and the standard data of the target user.

The second comparison result represents whether the user to be detected meets the standard of being the target user.

Still taking a bank application scenario as an example, the user to be detected determines that the identity data of the user to be detected corresponds to the new user, for example, by opening a bank account.

For example, the user data of the user to be detected may be determined according to the identity data of the user to be detected, and the second comparison result may be determined by comparing the target user standard data with the user data of the user to be detected.

In operation S370, according to the second comparison result, the target user identity data set update data is determined.

According to the data processing method applied to the first server side of the embodiment of the disclosure, under the condition that the identity data of the user to be detected corresponds to the new user, according to the identity data of the user to be detected and the standard data of the target user, the determined second comparison result can represent whether the user to be detected meets the standard of the target user, for example, the update data of the identity data set of the target user determined according to the second comparison result can be used for updating the identity data set of the target user, so that the real-time update of the identity data set of the target user is realized, and the updated identity data set of the target user is also convenient for accurately determining the user to be detected having a target association relationship with the target user.

Illustratively, the above-described operations S360 to S370 may be performed, for example, after the operation S350 or before the operation S350.

The disclosure also provides a data processing method applied to the second server side.

Fig. 5 schematically shows a flowchart of a data processing method 400 applied to the second server side according to an embodiment of the present disclosure.

In operation S410, user data of the first terminal or the second terminal is received via the first server side.

The second terminal is used for receiving the user prompt information.

It will be appreciated that the first terminal is user specific and that a user may log into the first terminal and record user data with the first terminal. The second terminal is for the worker, who may in some cases record the user data through the second terminal.

User data may be understood as data related to a user.

In operation S420, an inventory user knowledge graph is determined based on the user data.

The inventory user knowledge graph has been described in detail above and will not be described in detail here.

In operation S430, a target user identity data set is determined according to the inventory user knowledge graph and the target user standard data.

The target user identity data set comprises identity data of a target user, and the identity data of the target user is used for detecting the identity data of a user to be detected to obtain a first comparison result.

According to the data processing method applied to the second server side, the relation between the user data of the users at the stock and the user data can be clearly represented through the stock user knowledge graph determined by the user data, the stock user knowledge graph has expansibility and is convenient for data search and systematized data display, and the stock user knowledge graph determined by the data processing method applied to the second server side according to the embodiment of the disclosure can be used for determining first graph associated data related to the identity data of the target user or second graph associated data related to the identity data of the users to be detected. The target user identity data set can be accurately and completely determined from the stock user data through the stock user knowledge graph and the target user standard data.

It should be noted that "determining the stock user knowledge graph according to the user data" may be understood as determining the stock user knowledge graph only once, and then when the user data is updated, the stock user knowledge graph may be updated accordingly.

It should be noted that, still taking the banking application scenario as an example, the first server may be a server of a banking outlet, and the user transacts business at a specific outlet, and the user data comes from the banking outlet. The second server may be a server of a head office, and the user data of the inventory of users may be stored in a database of the head office.

Fig. 6 schematically shows a flowchart of a data processing method 500 applied to the second server side according to another embodiment of the present disclosure.

As shown in fig. 6, a data processing method 500 according to another embodiment of the present disclosure may further include: operation S540.

In operation S540, the target user identity data set is updated according to the target user identity data set update data.

According to the data processing method applied to the second server side in the embodiment of the disclosure, the target user identity data set is also updated according to the target user identity data set updating data, and the corresponding target user identity data can be updated in real time, so that the user to be detected having the target association relationship with the target user can be accurately determined.

Illustratively, operation S540 may be performed after operation S430 described above, for example.

As shown in fig. 6, the data processing method 500 applied to the second server according to another embodiment of the present disclosure may further include: operation S550 to operation S560.

In operation S550, the user data is classified, resulting in at least one of the following user data categories: user identity data, user service data, user identity association relationship data, and user representation data.

In operation S560, recommendation information index data is determined according to the user data category.

Illustratively, the recommendation information indicator data may include at least one of: user service data, user identity association relationship data and user portrait data.

According to the data processing method applied to the second server side, the user data can be sorted by classifying the user data, the obtained user data category can accurately and efficiently determine recommended information index data and the like, and the data processing efficiency is higher.

Illustratively, the operations S550 to S560 may be performed after the above-described operation S540 or before the operation S430, for example.

According to the data processing method applied to the second server side in the further embodiment of the present disclosure, the second server side and the first server side may perform message communication through at least one of the switch and the distributed message platform.

It can be understood that, in some application scenarios, the number of communication messages between the second server and the first server is large, which may affect the message communication speed between the second server and the first server, and decrease the message communication efficiency.

A switch may be understood as a device that expands the network and may provide more connection ports in a sub-network for connecting more computer devices.

A distributed message platform is understood to be a software platform that builds operations related to messages on a cluster of multiple hosts.

Illustratively, the distributed messaging platform may include: KAFKA distributed messaging platform.

According to the data processing method applied to the second server side in the embodiment of the disclosure, the message communication is performed between the second server side and the first server side through at least one of the switch and the distributed message platform, so that the message communication efficiency can be improved.

The disclosure also provides a data processing method, which can be applied to a third server side, for example.

Fig. 7 schematically illustrates a data processing method applied to a third server side according to an embodiment of the present disclosure, including operations S601 to S606.

In operation S601, user data of the first terminal or the second terminal is received.

In operation S602, an inventory user knowledge graph is determined based on the user data.

In operation S603, a target user identity data set is determined according to the inventory user knowledge graph and the target user standard data.

In operation S604, identity data of a user to be detected is determined in response to login information for a first terminal of the user.

In operation S605, the identity data of the user to be detected is compared with the identity data of the target user to obtain a first comparison result.

The target user identity data set comprises identity data of a target user;

in operation S606, when the first comparison result indicates that the identity data of the user to be detected and the identity data of the target user have the target association relationship, the user prompt information is determined according to the identity data of the user to be detected.

The target association includes at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

It should be noted that an execution main body of the data processing method in the embodiment of the present disclosure may be a third server, or may be a system including the first server and the second server, and a specific interaction process of related data is, for example, as shown in fig. 7, each operation is similar to the data processing method applied to the first server or the data processing method applied to the second server, and is not described again here.

Fig. 8 schematically shows a schematic diagram of a data processing method 700 applied to a third server according to another embodiment of the present disclosure.

Illustratively, the data processing method 700 applied to the third server side according to another embodiment of the present disclosure may further include operations S708 to S710.

In operation S708, the user data is classified into at least one of the following user data categories: user identity data, user service data, user identity association relationship data, and user representation data.

In operation S709, recommendation information index data is determined according to the user data category.

Illustratively, the recommendation information indicator data includes at least one of: user portrait data, user business data and user identity association relation data.

In operation S710, in a case that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship, determining user recommendation information according to recommendation information index data related to the identity data of the user to be detected.

Illustratively, operations S708 through S710 may be performed after operation S606 described above, for example.

Fig. 9 schematically shows a schematic diagram of a data processing method 800 applied to a third server according to yet another embodiment of the present disclosure.

Illustratively, the data processing method 800 applied to the third server side according to still another embodiment of the present disclosure may further include operations S811 to S813.

In operation S811, when the identity data of the user to be detected corresponds to the new user, a second comparison result is determined according to the identity data of the user to be detected and the target user standard data.

In operation S812, it is determined that the target user identity data set update data is updated according to the second comparison result.

In operation S813, the target user identity data set is updated according to the target user identity data set update data.

Illustratively, operations S811 to S813 may be performed after operation S606 described above, for example.

Fig. 10 schematically shows a data processing method according to another embodiment of the present disclosure, and a schematic diagram of data interaction between a first server and a second server is shown.

As shown in fig. 10, for example, in a data processing center 1001 on the second server side, user data 1002 as metadata may be processed to obtain a user data category 1003 and a stock user knowledge graph 1004. User business data 1005, user profile data 1006, and user identity association data 1007 may be determined from user data category 1003. At the switching network 1008 of the second server, data processing and interaction may be performed through a server cluster of the second server, and fig. 10 exemplarily shows that the server cluster of the second server includes N nodes from N1 to Nn. Each node is in communication connection with a switch, and each switch is in message communication with the distributed message platform KAFKA.

In the example of fig. 10, a switching network 1008 of the second server side is also schematically shown, the server cluster comprising i nodes for data processing of N1 to Ni, each node for data processing of the first server side being in message communication with a distributed message platform KAFKA, the nodes for data processing being in communication connection with the first server.

Taking a bank application scenario as an example, the first server side corresponds to each branch point of a branch, the second server side corresponds to a head office, and the update frequency of the inventory user data knowledge graph can be set to be in a range from 1 day/time to 1 month/time, for example.

Fig. 11 schematically shows a data interaction between a first server and a first terminal and a second terminal in a case of a banking application scenario according to a data processing method according to a further embodiment of the present disclosure.

As shown in fig. 11, data interaction is performed between a first server 1101 and a second server, for example, a target user identity data set and recommendation information index data determined by the second server may be sent to a database 1102 corresponding to the first server, for example, these data may be communicated and interacted between a handheld terminal device 1104 (a second terminal for a staff member) of a website, for example, a tablet computer, by a wireless route 1103, and these data may also be communicated and interacted between a number caller 1107 and an intelligent machine 1106 (a first terminal for a user) supporting a transaction service of the website by a wired route 1105.

In a banking application scenario, for example, for the transaction of non-large account transfer services or complex services, a worker at a website generally assists a user client in completing services including account password modification, personal client basic information update, card loss reporting and subsidizing on an intelligent machine.

In summary, the data processing method applied to the first server, the data processing method applied to the second server, and the data processing method according to the embodiments of the present disclosure may achieve at least one of the following technical effects in a banking application scenario:

1) And the user having the target association relationship with the target user actually carries the identity attribute of the target user, and the related staff can recommend the differentiated asset service at the right moment after the user arrives at the store. The embodiment of the disclosure can dynamically update the target user identity data set through the stock user knowledge graph, and has higher data processing efficiency. For example, a worker may be assisted in accurately servicing a target user and users having a target association with the target user.

2) Through the interaction between the first server side and the second server side and the interaction between the first server side and the first terminal and the second terminal, the bidirectional synchronization of data can be realized at the first server side (website side), the consistency and the effectiveness of data such as a target user identity data set and the like of each website are ensured, and relevant workers can conveniently and accurately determine user recommendation information in a unified manner.

3) For a target user or a user who has a target association relation with the target user and arrives at a store, the embodiment of the disclosure can recommend information to the user in a targeted and accurate manner, for example, recommendation information such as financial products can be recommended to the user, so that differentiated services can be better achieved, and experience of the user can be effectively improved.

4) The target user identity data set and the recommendation information index data can be processed in batches at the second server side (corresponding to a head office) and then sent to the first server side (each website), so that the high-efficiency pushing with customized batch frequency is realized, the automation is higher, and a large amount of manpower resources and manual maintenance errors are saved.

Based on the application method, the disclosure also provides a data processing device applied to the first server side, a data processing device applied to the second server side and a data processing device applied to the third server side. The device will be described in detail below with reference to fig. 12, 13, and 14, respectively.

Fig. 12 schematically shows a block diagram of a data processing apparatus 1200 applied to the first server side according to an embodiment of the present disclosure.

As shown in fig. 12, the data processing apparatus 800 applied to the first server side of this embodiment includes: the system comprises an identity data determining module 1210 of the user to be detected, a first comparison result determining module 1220 and a user prompt information determining module 1230.

The identity data determining module 1210 of the user to be detected is configured to determine the identity data of the user to be detected in response to the login data of the first terminal of the user.

The first comparison result determining module 1220 is configured to compare the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result.

The user prompt information determining module 1230 is configured to determine the user prompt information according to the identity data of the user to be detected when the first comparison result indicates that the identity data of the user to be detected and the identity data of the target user have the target association relationship.

According to still another embodiment of the present disclosure, the first comparison result determining module may include: the map associated data determining submodule and the comparing submodule.

And the map associated data determining submodule is used for determining first map associated data related to the identity data of the target user or determining second map associated data related to the identity data of the user to be detected according to the stock user knowledge map, wherein the stock user knowledge map represents the related data of the user.

And the comparison sub-module is used for comparing the identity data of the user to be detected with the first map associated data or comparing the identity data of the target user with the second map associated data to obtain a first comparison result.

The data processing apparatus applied to the first server according to another embodiment of the present disclosure may further include: and a recommended information index data determining module.

And the recommendation information index data determining module is used for determining user recommendation information according to the recommendation information index data related to the identity data of the user to be detected under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship.

The recommendation information indicator data comprises at least one of: user portrait data, user business data and user identity association relationship data.

The data processing apparatus applied to the first server according to another embodiment of the present disclosure may further include: a second comparison result determination module and an update data determination module. The target user identity data set includes identity data of the target user.

And the second comparison result determining module is used for determining a second comparison result according to the identity data of the user to be detected and the standard data of the target user under the condition that the identity data of the user to be detected corresponds to the new user.

And the update data determining module is used for determining the update data of the target user identity data set according to the second comparison result.

Fig. 13 schematically shows a block diagram of a data processing apparatus 1300 applied to the second server side according to an embodiment of the present disclosure.

As shown in fig. 13, the data processing apparatus 1300 applied to the second server side of the embodiment includes: a user data determination module 1310, an inventory user knowledge graph determination module 1320, and a target user identity data set determination module 1330.

The user data determining module 1310 is configured to receive user data of the first terminal or the second terminal via the first server. The second terminal is used for receiving the user prompt information.

An inventory user knowledge graph determining module 1320, configured to determine an inventory user knowledge graph according to the user data.

The target user identity data set determining module 1330 is configured to determine a target user identity data set according to the inventory user knowledge graph and the target user standard data.

The data processing apparatus applied to the second server according to another embodiment of the present disclosure may further include: and the target user identity data set updating module.

And the target user identity data set updating module is used for updating the target user identity data set according to the target user identity data set updating data.

The data processing apparatus applied to the second server according to another embodiment of the present disclosure may further include: the system comprises a user data classification module and a recommendation information index data determination module.

The user data classification module is used for classifying the user data to obtain at least one of the following user data categories: user identity data, user service data, user identity association relationship data, and user representation data.

And the recommendation information index data determining module is used for determining recommendation information index data according to the user data category.

According to another embodiment of the present disclosure, the data processing apparatus applied to the second server side performs message communication with the first server side through at least one of the switch and the distributed message platform.

Fig. 14 schematically shows a block diagram of a data processing apparatus 1400 applied to the second server side according to an embodiment of the present disclosure.

As shown in fig. 14, the data processing apparatus 1400 applied to the second server side of the embodiment includes: a receiving module 1410, a first determining module 1420, a second determining module 1430, a third determining module 1440, a comparing module 1450, and a fourth determining module 1460.

A receiving module 1410, configured to receive user data of the first terminal or the second terminal.

A first determining module 1420, configured to determine an inventory user knowledge graph according to the user data.

The second determining module 1430 is configured to determine a target user identity data set according to the inventory user knowledge graph and the target user standard data.

The third determining module 1440 is configured to determine, in response to the login information of the first terminal for the user, the identity data of the user to be detected.

The comparing module 1450 is configured to compare the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result.

The target user identity data set includes identity data of the target user.

A fourth determining module 1460, configured to determine, according to the identity data of the user to be detected, user prompt information when the first comparison result indicates that the identity data of the user to be detected and the identity data of the target user have a target association relationship.

According to the embodiment of the present disclosure, any of the identity data determination module 1210, the first comparison result determination module 1220, the user prompt information determination module 1230, the user data determination module 1310, the stock user knowledge graph determination module 1320, the target user identity data set determination module 1330, the receiving module 1410, the first determination module 1420, the second determination module 1430, the third determination module 1440, the comparison module 1450, and the fourth determination module 1460 of the user to be detected may be combined into one module to be implemented, or any one of them may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to the embodiment of the present disclosure, at least one of the identity data determining module 1210, the first comparison result determining module 1220, the user prompt information determining module 1230, the user data determining module 1310, the inventory user knowledge graph determining module 1320, the target user identity data set determining module 1330, the receiving module 1410, the first determining module 1420, the second determining module 1430, the third determining module 1440, the comparing module 1450, and the fourth determining module 1460 of the user to be detected may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by any one of three implementations of software, hardware, and firmware or any suitable combination of any of them. Alternatively, at least one of the identity data determination module 1210, the first comparison result determination module 1220, the user prompt information determination module 1230, the user data determination module 1310, the inventory user knowledge graph determination module 1320, the target user identity data set determination module 1330, the receiving module 1410, the first determination module 1420, the second determination module 1430, the third determination module 1440, the comparison module 1450, and the fourth determination module 1460 of the user to be detected may be implemented at least in part as a computer program module that, when executed, may perform corresponding functions.

It should be understood that the embodiments of the apparatus part of the present disclosure are the same as or similar to the embodiments of the method part of the present disclosure, and the technical problems to be solved and the technical effects to be achieved are also the same as or similar to each other, and the detailed description of the present disclosure is omitted.

Fig. 15 schematically shows a block diagram of an electronic device suitable for implementing the data processing method applied to the first server side, the data processing method applied to the second server side, and the data processing method according to an embodiment of the present disclosure.

As shown in fig. 15, an electronic device 1500 according to an embodiment of the present disclosure includes a processor 1501 which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1502 or a program loaded from a storage section 1508 into a Random Access Memory (RAM) 1503. Processor 1501 may include, for example, a general purpose microprocessor (e.g., CPU), an instruction set processor and/or associated chipsets and/or a special purpose microprocessor (e.g., application Specific Integrated Circuit (ASIC)), or the like. The processor 901 may also include on-board memory for caching purposes. The processor 901 may comprise a single processing unit or a plurality of processing units for performing the different actions of the method flows according to embodiments of the present disclosure.

In the RAM1503, various programs and data necessary for the operation of the electronic apparatus 1500 are stored. The processor 1501, the ROM 1502, and the RAM1503 are connected to each other by a bus 1504. The processor 1501 executes various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 1502 and/or RAM 1503. Note that the program may also be stored in one or more memories other than the ROM 1502 and the RAM 1503. The processor 1501 may also execute various operations of the method flows according to embodiments of the present disclosure by executing programs stored in one or more memories.

According to an embodiment of the present disclosure, electronic device 1500 may also include input/output (I/O) interface 1505, input/output (I/O) interface 1505 also being connected to bus 1504. The electronic device 1500 may also include one or more of the following components connected to the I/O interface 1505: an input portion 1506 including a keyboard, a mouse, and the like; an output portion 1507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 1508 including a hard disk and the like; and a communication section 1509 including a network interface card such as a LAN card, a modem, or the like. The communication section 1509 performs communication processing via a network such as the internet. A drive 1510 is also connected to the I/O interface 1505 as needed. A removable medium 1511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1510 as necessary, so that a computer program read out therefrom is mounted into the storage section 1508 as necessary.

The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.

According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may include one or more memories other than ROM 1502 and/or RAM1503 and/or ROM 1502 and RAM1503 described above according to embodiments of the present disclosure.

Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method illustrated in the flow chart. When the computer program product runs in a computer system, the program code is used for causing the computer system to realize the method provided by the embodiment of the disclosure.

The computer program performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure when executed by the processor 1501. The above described systems, devices, modules, units, etc. may be implemented by computer program modules according to embodiments of the present disclosure.

In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, and the like. In another embodiment, the computer program may also be transmitted in the form of a signal, distributed over a network medium, downloaded and installed via the communication section 1509, and/or installed from the removable media 1511. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1509, and/or installed from the removable medium 1511. The computer program, when executed by the processor 1501, performs the above-described functions defined in the system of the embodiments of the present disclosure. The above described systems, devices, apparatuses, modules, units, etc. may be implemented by computer program modules according to embodiments of the present disclosure.

In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments of the present disclosure and/or the claims may be made without departing from the spirit and teachings of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.

The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims

1. A data processing method applied to a first server side comprises the following steps:

determining identity data of a user to be detected in response to login data of a first terminal of the user;

comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result; and

determining user prompt information according to the identity data of the user to be detected under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship, wherein the target association relationship comprises at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

2. The method according to claim 1, wherein the comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result comprises:

determining first map associated data related to the identity data of the target user or determining second map associated data related to the identity data of the user to be detected according to the stock user knowledge map, wherein the stock user knowledge map represents the related data of the user; and

and comparing the identity data of the user to be detected with the first map associated data or comparing the identity data of the target user with the second map associated data to obtain the first comparison result.

3. The method of claim 2, further comprising:

determining user recommendation information according to recommendation information index data related to the identity data of the user to be detected under the condition that the first comparison result represents that the identity data of the user to be detected and the identity data of the target user have a target association relationship, wherein the recommendation information index data comprises at least one of the following data: user portrait data, user business data and user identity association relation data.

4. The method of any of claims 1-3, wherein a target user identity data set includes identity data of the target user, the method further comprising:

under the condition that the identity data of the user to be detected corresponds to a new user, determining a second comparison result according to the identity data of the user to be detected and standard data of a target user, wherein the second comparison result represents whether the user to be detected reaches the standard of the target user or not; and

and determining the update data of the target user identity data set according to the second comparison result.

5. A data processing method applied to a second server side comprises the following steps:

receiving user data of a first terminal or a second terminal through a first server, wherein the second terminal is used for receiving user prompt information;

determining an inventory user knowledge graph according to the user data; and

and determining a target user identity data set according to the stock user knowledge graph and the target user standard data, wherein the target user identity data set comprises identity data of a target user, and the identity data of the target user is used for detecting the identity data of a user to be detected to obtain a first comparison result.

6. The method of claim 5, further comprising:

and updating the target user identity data set according to the target user identity data set updating data.

7. The method of claim 5, further comprising:

classifying the user data to obtain at least one of the following user data categories: user identity data, user service data, user identity association relation data and user portrait data; and

and determining recommended information index data according to the user data category.

8. The method of any of claims 5-7, wherein the second server side is in messaging communication with the first server side through at least one of a switch, a distributed messaging platform.

9. A data processing method applied to a third server side comprises the following steps:

receiving user data of a first terminal or a second terminal;

determining an inventory user knowledge graph according to the user data;

determining a target user identity data set according to the stock user knowledge graph and the target user standard data;

responding to login information of the first terminal aiming at the user, and determining identity data of the user to be detected;

comparing the identity data of the user to be detected with the identity data of a target user to obtain a first comparison result, wherein the target user identity data set comprises the identity data of the target user;

10. A data processing apparatus applied to a first server side, comprising:

the identity data determining module of the user to be detected is used for responding to login data of a first terminal of the user and determining the identity data of the user to be detected;

the first comparison result determining module is used for comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result; and

a user prompt information determination module, configured to determine user prompt information according to the identity data of the user to be detected when the first comparison result indicates that the identity data of the user to be detected and the identity data of the target user have a target association relationship, where the target association relationship includes at least one of the following categories: identity, relationship of blood relationship attributes and relationship of social attributes.

11. A data processing apparatus applied to a second server side, comprising:

the user data determining module is used for receiving the user data of the first terminal or the second terminal through the first server;

the stock user knowledge graph determining module is used for determining the stock user knowledge graph according to the user data; and

and the target user identity data set determining module is used for determining a target user identity data set according to the stock user knowledge graph and the target user standard data, wherein the target user identity data set comprises identity data of a target user, and the identity data of the target user is used for detecting the identity data of a user to be detected to obtain a first comparison result.

12. A data processing apparatus applied to a third server side, comprising:

the receiving module is used for receiving user data of the first terminal or the second terminal;

the first determining module is used for determining the stock user knowledge graph according to the user data;

the second determining module is used for determining a target user identity data set according to the stock user knowledge graph and the target user standard data;

the third determining module is used for responding to the login information of the first terminal aiming at the user and determining the identity data of the user to be detected;

the comparison module is used for comparing the identity data of the user to be detected with the identity data of the target user to obtain a first comparison result, wherein the target user identity data set comprises the identity data of the target user;

a fourth determining module, configured to determine user prompt information according to the identity data of the user to be detected when the first comparison result indicates that the identity data of the user to be detected and the identity data of the target user have a target association relationship, where the target association relationship includes at least one of the following categories: the relationship is the same, the relationship of blood relationship attributes and the relationship of social attributes.

13. An electronic device, comprising:

one or more processors;

a storage device for storing one or more programs,

wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-9.

14. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 9.

15. A computer program product comprising a computer program stored on at least one of a readable storage medium and an electronic device, the computer program when executed by a processor implementing the method according to any one of claims 1-9.