CN110402570B

CN110402570B - Information processing method and system, server, terminal, computer storage medium

Info

Publication number: CN110402570B
Application number: CN201780054468.0A
Authority: CN
Inventors: 陈谦
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2017-11-03
Filing date: 2017-11-03
Publication date: 2020-08-11
Anticipated expiration: 2037-11-03
Also published as: WO2019084922A1; CN110402570A

Abstract

The embodiment of the invention discloses an information processing method and system, a server, a terminal and a computer storage medium. The method comprises the following steps: requesting to access a second application client based on account data of a first application client, and obtaining a first message from a first terminal comprising the first application client; the first message comprises a user identity corresponding to account data of the first application client; obtaining user credit data associated with the user identity, and sending the user credit data to a second terminal comprising the second application client so as to enable the second application client to execute corresponding service logic based on the user credit data; the first terminal and the second terminal are the same or different; the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

Description

Information processing method and system, server, terminal, computer storage medium

Technical Field

The present invention relates to information processing technologies, and in particular, to an information processing method and system, a server, a terminal, and a computer storage medium.

Background

With the rapid development of internet technology, the internet plays an increasingly greater role in people's lives, and people can use the internet to process various matters. But typically an account registration or the like is required before using the internet service. In order to avoid the trouble brought to the user by excessive account registration, a technical scheme of using the account number of one existing application to authorize and log in another application is provided, namely, the user can use the service provided by the third-party application in an account number authorization mode based on the account number of one registered application, so that the user is not required to repeatedly register the account under a plurality of applications.

Disclosure of Invention

The embodiment of the invention provides an information processing method and system, a server, a terminal and a computer storage medium.

In order to achieve the above purpose, the technical solution of the embodiment of the present invention is realized as follows:

the embodiment of the invention provides an information processing method, which comprises the following steps: requesting to access a second application client based on account data of a first application client, and obtaining a first message from a first terminal comprising the first application client; the first message comprises a user identity corresponding to the account data of the first application client; obtaining user credit data associated with the user identity, and sending the user credit data to a second terminal comprising the second application client so as to enable the second application client of the second terminal to execute corresponding service logic based on the user credit data; the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

The embodiment of the invention also provides an information processing method, which comprises the following steps: based on a request for accessing a second application client by using the account data of the first application client, obtaining user credit data corresponding to the account data of the first application client, wherein the user credit data is used for representing the probability that an end user corresponding to the user identity mark violates a predetermined rule; executing, by the second application client, corresponding service logic based on the user credit data.

The embodiment of the invention also provides an information processing method, which comprises the following steps: based on a request for accessing a second application client with account data of the first application client, a server obtains a first message from a first terminal including the first application client; the first message comprises a user identity corresponding to account data of the first application client; the server obtains user credit data associated with the user identity and sends the user credit data to a second terminal comprising the second application client; the first terminal and the second terminal are the same or different; the user credit data is used for representing the probability that the terminal user corresponding to the user identity label violates a preset rule; and based on the user credit data, the second terminal executes corresponding service logic through the second application client.

An embodiment of the present invention further provides a server, where the server includes: the system comprises a first communication unit, a first acquisition unit and a second communication unit; the first communication unit is configured to request to access a second application client based on account data of a first application client, and obtain a first message from a first terminal including the first application client; the first message comprises a user identity corresponding to the account data of the first application client; the first acquisition unit is configured to acquire user credit data associated with the user identity; the user credit data is used for representing the probability that the terminal user corresponding to the user identity label violates a preset rule; the second communication unit is configured to send the user credit data obtained by the first obtaining unit to a second terminal including the second application client, so that the second application client of the second terminal executes corresponding service logic based on the user credit data.

An embodiment of the present invention further provides a terminal, where the terminal includes: a third communication unit and an execution unit; the third communication unit is configured to access a second application client based on account data of a first application client, and obtain user credit data corresponding to the account data of the first application client, where the user credit data is used to represent a probability that an end user corresponding to the user identity identifier violates a predetermined rule; the execution unit is configured to execute a corresponding service logic through the second application client based on the user credit data obtained by the third communication unit.

The embodiment of the invention also provides a computer storage medium, on which computer instructions are stored, and the instructions are executed by a processor to realize the steps of the information processing method applied to the server in the embodiment of the invention; or, the instructions are executed by the processor to implement the steps of the information processing method applied to the terminal according to the embodiment of the present invention.

The embodiment of the invention also provides a server, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the program, the steps of the information processing method applied to the server are realized.

The embodiment of the invention also provides a terminal, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the steps of the information processing method applied to the terminal.

The embodiment of the invention also provides an information processing system, which comprises a server and a terminal; the server is configured to request access to a second application client based on account data of the first application client, and the server obtains a first message from the terminal or another terminal comprising the first application client; the first message comprises a user identity corresponding to account data of the first application client; obtaining user credit data associated with the user identity, and sending the user credit data to the terminal comprising the second application client; the user credit data is used for representing the probability that the terminal user corresponding to the user identity label violates a preset rule; the terminal is configured to execute corresponding service logic through the second application client based on the user credit data.

Drawings

FIG. 1 is a schematic view of an interaction flow for logging in a third party application based on authorization of a master application;

FIG. 2 is a system architecture diagram illustrating information interaction according to an embodiment of the present invention;

FIG. 3 is a first flowchart of an information processing method according to an embodiment of the present invention;

FIG. 4 is a second flowchart of an information processing method according to an embodiment of the present invention;

FIG. 5 is a third flowchart illustrating an information processing method according to an embodiment of the invention;

FIG. 6a and FIG. 6b are schematic interaction flow diagrams of an information processing method according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of a component structure of a server according to an embodiment of the present invention;

FIG. 8 is a schematic diagram of another configuration of a server according to an embodiment of the present invention;

fig. 9 is a schematic structural diagram of a terminal according to an embodiment of the present invention;

FIG. 10 is a diagram illustrating a hardware configuration of a server according to an embodiment of the present invention;

fig. 11 is a diagram illustrating software and hardware combination of a terminal according to an embodiment of the present invention.

Detailed Description

Before describing the information processing method in detail, a process of logging in a third-party application based on the authorization of a main application is described first. FIG. 1 is a schematic view of an interaction flow for logging in a third party application based on authorization of a master application; as shown in fig. 1, includes:

step 101: and the main application client sends a login request to the third-party application client, wherein the login request is specifically used for requesting to login the third-party application client by using the account of the main application client. The login request includes a User identity, which may be a User Identity (UID) uniquely corresponding to a User account of the primary application client.

In practical applications, as an example, a user opens a web page using a browser application client, for example, the web page is an e-commerce page or a multimedia playing page (e.g., an Tencent video page); the user needs to log in to the web page. In order to avoid that the user needs to input more information content to register and input a user name and a password to log in, one or more icons of the main application, such as a QQ application icon, a WeChat application icon and the like, are configured in the login area of the page, so that the user can log in the webpage by using the account number of the existing main application. When a user clicks an icon of any main application, a main application client corresponding to the icon as the main application initiates a login request to a browser application client as a third-party application client.

Step 102: the third party application client requests a temporary Identifier from a main application server corresponding to the main application client based on a login request of the main application client, wherein the temporary Identifier can be a temporary Universal Unique Identifier (UUID), and the temporary UUID is only effective for the request; or the temporary UUID is valid for a preset time frame (e.g., five minutes). Wherein, the request message may include the user identity of the primary application client; the temporary identifier generated by the primary application server corresponds to the user identity of the primary application client.

Step 103: and the main application server returns the temporary identifier to the third-party application client.

Step 104: and the third party application client generates a graphic Code based on the temporary identifier and the application identifier (APP ID), displays the graphic Code, and specifically, the graphic Code can be a two-dimensional Code (QR Code), so that the third party application client generates and displays the two-dimensional Code according to the obtained temporary UUID and the application identifier Code of the third party application client.

Step 105: the third party application client side polls the main application server to obtain information whether the user confirms authorization, wherein the information carries temporary identification; step 104 and step 105 are not in sequence, and may be performed first in step 104 and then in step 105, or may be performed first in step 105 and then in step 104, or may be performed in step 104 and step 105 at the same time, where the execution sequence is not limited in this embodiment.

Step 106: and the main application client scans the graphic code displayed by the third-party application client to obtain the temporary identifier and the application identifier carried by the graphic code. The main application client has a graphic code scanning and reading function, and after the function is activated, as an implementation mode, an image containing a graphic code is obtained by calling a camera, and a temporary identifier and an application identifier carried by the graphic code in the image are further identified. For example, the main application client starts a graphic code scanning function and calls a camera to enable the main application client to display a display interface comprising a scanning frame; when the camera collects image data so that the collected graphic code is in the scanning frame, the main application client scans the collected graphic code based on the graphic code scanning function to obtain a temporary identifier and an application identifier carried by the graphic code. As another implementation, the master application client has an Optical Character Recognition (OCR) function, that is, directly recognizes characters in an image containing a graphic code, and further obtains a temporary identifier and an application identifier carried by the graphic code based on the recognized characters.

Step 107: and the main application client informs the main application server, the notification is used for requesting to log in the third-party application by using the account number of the main application client, the notification message carries the temporary identifier, the application identifier and the user identity identifier which are obtained by scanning, and the application identifier is the identifier of the third-party application client.

Step 108: the main application server returns authorization information to the third-party application client based on the notification message, and carries an access token (access token).

Step 109: the main application client confirms authorization to the third-party application client, in practical application, a display interface of the main application client can display virtual keys such as authorization and unauthorized, a user clicks the virtual key for authorization, namely the main application client confirms authorization to the third-party application client, and the third-party application client allows login by using an account of the main application client. Correspondingly, if the user clicks the "unauthorized" virtual key, it is determined that the main application client does not confirm authorization to the third-party application client, and the third-party application client does not allow the user to log in by using the account of the main application client.

Step 110: after the authorization is confirmed, the third-party application client sends an information acquisition request to the main application server, the information acquisition request comprises information such as temporary identification, an access token and application identification, the main application server can determine the user identity identification of the corresponding main application client based on the temporary identification in the information acquisition request, acquire corresponding user information based on the user identity identification, and return the user information to the third-party application.

The main application client and the third-party application client are client application programs installed in the terminal equipment, and different client application programs can provide different services after being activated; the main application server is a server corresponding to the main application client. The primary application client may be one of the following application types: an instant messaging application client, a social application client, a payment platform client, which may be, for example, a WeChat application, a QQ application, a Facebook application, a micro blog (Weibo) application. The main application client and the third party application client can run in the same terminal device or different terminal devices.

The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.

Fig. 2 is a schematic diagram of hardware entities performing information interaction in the embodiment of the present invention, where fig. 1 includes: the system comprises a server 11, a server 12 and terminal devices 21-23, wherein the terminal devices 21-23 perform information interaction with the server 11 or the server 12 through a wired network or a wireless network, and the terminal devices comprise mobile phones, tablet computers, desktop computers, notebook computers and the like. In one example, at least one of the terminal devices 21-23 may run a first application client and a second application client, i.e. the first application client and the second application client may run in the same terminal device at the same time; in another example, one of the terminal devices 21-23 may run a first application client and the other terminal device may run a second application client, i.e. the first application client and the second application client are run in different terminal devices, respectively. The server 11 and the server 12 are respectively a server to which the first application client belongs and a server to which the second application client belongs, and the application run by the terminal device can provide corresponding services through information interaction between the terminal device and the servers.

The above example of fig. 1 is only an example of a system architecture for implementing the embodiment of the present invention, and the embodiment of the present invention is not limited to the system architecture described in fig. 1, and various embodiments of the present invention may be proposed based on the system architecture.

The embodiment of the invention provides an information processing method. FIG. 3 is a first flowchart of an information processing method according to an embodiment of the present invention; as shown in fig. 3, the method includes:

step 301: requesting to access a second application client based on account data of a first application client, and obtaining a first message from a first terminal comprising the first application client; the first message comprises a user identity corresponding to the account data of the first application client.

Step 302: obtaining user credit data associated with the user identity, and sending the user credit data to a second terminal comprising the second application client so as to enable the second application client of the second terminal to execute corresponding service logic based on the user credit data; the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

In this embodiment, the information processing method is applied to a server, which may specifically be a server to which a first application client belongs, that is, the first application client requests to access a second application client by account data of the first application client, and the first application client sends a first message to the server through a first terminal, where the first message includes a user identity identifier corresponding to the account data of the first application client; the user identity may be a UID that uniquely corresponds to the account data of the first application client.

In this embodiment, the obtaining a first message from a first terminal including a first application client based on a request for accessing a second application client by using account data of the first application client includes: and obtaining a first message from the first terminal based on the first terminal reading and identifying the identification information output by the second terminal through the second application client through the first application client, wherein the first message comprises the user identity identification and the temporary identification distributed by the server. The identification information is a graphic code, such as a two-dimensional code, a bar code, and the like.

In practical applications, the first terminals are the same or different, that is, the first application client and the second application client may be installed in the first terminal and the second terminal, respectively, or may be installed in the same terminal. Taking the same first terminal and the same second terminal as an example, after the terminal activates the second application client, the terminal can access the second application client by the account data of the first application client through detecting the input operation request aiming at the identifier of the first application client in the display interface of the second application client; the displayed identifier of the first application client may specifically be a displayed icon or link of the first application client, and the user triggers the icon or link to request access to the corresponding second application client by using the account data of the first application client. After receiving the request, the second application client communicates with the server (i.e., the server to which the first application client belongs) to obtain a temporary identifier assigned by the server, where the temporary identifier may be a UUID. As an implementation manner, the second application client may encode the temporary identifier in an encoding manner to generate identifier information, and output and display the identifier information; the first application client identifies the identification information and obtains a temporary identification included by the identification information; the second application client can encode the temporary identifier in a two-dimensional code encoding mode to generate two-dimensional code information, and the two-dimensional code information is displayed through a display assembly of the terminal; the first application client can recognize the two-dimension code information in an OCR mode, so that the temporary identifier carried by the two-dimension code information is obtained. At this time, the terminal sends a first message to the server through the first application client, where the first message includes a user identity corresponding to the account data of the first application client, and may also include the temporary identifier and an application identifier (the application identifier is an application identifier corresponding to the second application client), so that the server returns authorization information to the second application client of the terminal, and returns user credit data to the second application client of the second terminal according to the user identity and the corresponding user credit data obtained by the user identity.

In this embodiment, the sending the user credit data to the second terminal including the second application client includes: and responding to the obtained characterization confirmation message for confirming authorization to access the second application client by the account number data of the first application client, and sending the user credit data to the second application client.

As an implementation manner, a first terminal reads identification information output by a second application client through a first application client to obtain a temporary identification, the representation authorizes to access the second application client by account data of the first application client, that is, after the first application client of the first terminal obtains the temporary identification, a first message carrying a user identity is sent to a server, and in response to the first message, the server sends the obtained user credit data associated with the user identity to the second application client.

As another embodiment, the server may determine to obtain a confirmation message indicating that the first terminal determines to authorize to access the second application client with the account data of the first application client by receiving an input operation for the "confirm authorization" function key, that is, the server receives a confirmation message indicating that the first terminal determines to authorize to access the second application client with the account data of the first application client. In practical application, after the server receives a first message from the first terminal, based on information (including a temporary identifier, a second application client identifier, and a user identity identifier) carried in the first message, authorization information and an access token are sent to a second terminal including a second application client, the second terminal outputs and displays an interface including a "confirm authorization" function key based on the second application client, the user can determine authorization to access the second application client by using account number data of the first application client by clicking the "confirm authorization" function key, after receiving a confirm authorization instruction, the second application client notifies the server, and based on a notification message representing confirm authorization, the server sends user credit data associated with the user identity identifier to the second terminal, it can be understood that, in this embodiment, when the second application client needs the user credit data, corresponding user credit data is obtained from the server.

In this embodiment, the user credit data may include at least one of the following data types: credit score, credit rating. In one embodiment, a higher credit score or credit rating indicates a lower probability that the corresponding end user violates the agreed upon rule, and a lower credit score or credit rating indicates a higher probability that the corresponding end user violates the agreed upon rule.

In this embodiment, as an implementation manner, the server has a credit data calculation function, that is, the server may calculate and obtain the user credit data by collecting the behavior data, and when receiving the first message carrying the user identity, the server may search based on a user credit data set stored in the server, so as to obtain the user credit data associated with the user identity. As another embodiment, the user credit data may be obtained by the credit service platform through calculation by collecting behavior data, and after obtaining the first message, the server performs information interaction with the credit service platform to obtain the user credit data associated with the user identity from the credit service platform.

By adopting the technical scheme of the embodiment of the invention, under the condition that the first application client requests to access the second application client by the account data of the first application client, the server sends the user credit data corresponding to the account data to the second application client, so that the second application client can execute corresponding service logic based on the user credit data, the corresponding service is provided based on the probability condition violating the preset rule, the probability of safety problems such as information leakage or attack to a service platform and the like caused by a user with high probability of not complying with the preset rule in the process of obtaining the service is reduced, and the safety and reliability of service provision and the service platform are improved.

The embodiment of the invention also provides an information processing method, which is applied to a server, wherein the server can be specifically a server to which the first application client belongs. FIG. 4 is a second flowchart of an information processing method according to an embodiment of the present invention; as shown in fig. 4, the method includes:

step 401: and acquiring behavior data corresponding to the account data, wherein the behavior data comprises online behavior data and offline behavior data based on the Internet. The account data is account data of the first application client.

Step 402: and acquiring a first characteristic variable of the account data according to the behavior data, wherein the first characteristic variable is used for representing the behavior characteristic of the account data.

Step 403: inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable.

Step 404: requesting to access a second application client based on account data of a first application client, and obtaining a first message from a first terminal comprising the first application client; the first message includes a user identity of account data of the first application client.

Step 405: obtaining user credit data associated with the user identity, and sending the user credit data to a second terminal comprising the second application client so as to enable the second application client of the second terminal to execute corresponding service logic based on the user credit data; the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

In this embodiment, the first characteristic variable is used to represent the behavior characteristics of the account data, the behavior characteristics of the account data are obtained based on the account data based on the behavior data of the internet, and the probability value that the behavior of the account data does not satisfy the preset condition is obtained after the first characteristic variable is input to the data analysis model. Because the behavior data of the account data in the social application can cover the behavior of the account data more widely, the behavior data input into the data analysis model can comprehensively reflect the behavior of the account data, and the probability value that the behavior of the account data analyzed does not meet the preset condition is more accurate.

Specifically, the behavior data includes account data, internet-based online behavior data and offline behavior data.

Internet online behavior data includes, but is not limited to:

1) basic demographic attribute information of the user, such as name, age, gender, region, academic calendar, occupation, and the like;

2) virtual value-added service data, such as virtual account role decoration, game prop purchase, movie and television member service, cloud storage space value-added service, music flow package and the like;

3) social interaction behavior data, such as chatting, e-mail, voice call, microblog space posting, bean comment commenting, question answering, public number article reading and the like;

4) economic activity data, such as payments, financing, shopping, stocks, funds, P2P, finance, etc.;

5) entertainment and leisure behavior data such as video on demand, music playing, karaoke, news reading and the like;

6) educational behavior data, such as online reading, public class learning, professional examination practice, skill training, translation software use, and the like;

7) other internet mobile application behavior data, such as APP downloads, searches, etc.

The online data can be acquired by collecting data filled by a user or actively reporting an application program through an instant messaging application program, a game client, an APP downloading platform, a financial platform, shopping software and the like on a mobile phone, a tablet computer or a PC computer of the user.

Downstream data includes, but is not limited to:

1) online to Offline (O2O, Online to Offline) life service information, such as housekeeping services, urban services, beauty and health care, etc.;

2) wearable device data, such as medical health, exercise, etc.;

3) location Based Service (LBS) geographic Location data, such as navigation, check-in, special car, etc.;

4) travel data, such as ticket order, hotel reservations, etc.

Therefore, the probability values obtained according to the behavior data reflect the real probability values of the account numbers more accurately. In addition, when the behavior data changes, the behavior data is fed back to the server or is obtained by the server instantly, so that the updating speed of the behavior data is high, and the probability value obtained according to the instantly updated behavior data can reflect the probability that the current behavior of the account data does not meet the preset condition. The probability value that does not satisfy the preset condition may be a default probability, such as noncompliance with contractually specified behaviors, or the like.

For example, when the credit rating of the user a is obtained according to the behavior data of the user a, an account chat behavior of the user a in the instant messaging application, a behavior of watching a video in the video application, a behavior of downloading the application, and the like may be collected. First characteristic variables in the behavior data are respectively extracted, and the first characteristic variables of different categories can be obtained. Such as the first characteristic variable of the instant messaging class, the first characteristic variable of the video class and the first characteristic variable of the download class, all of the first characteristic variables of the different classes are input into the data analysis model, and a first numerical value is output. Inputting portions of the different classes of first characteristic variables into the data analysis model may also be employed.

In general, the friend of the user a has a similar point to the user a, and the behavior data of the friend of the user a can also reflect the probability that the behavior of the user a does not satisfy the preset condition. Thus, while inputting the first feature variable to the data analysis model, feature variables associated with friends of user a may also be simultaneously input.

Namely, the inputting the first characteristic variable into the data analysis model includes: acquiring a second characteristic variable, wherein the second characteristic variable is used for representing behavior characteristics of a plurality of other account data having an association relationship with the account data; inputting the first characteristic variable and the second characteristic variable into the data analysis model, wherein the data analysis model is further configured to output the user credit data according to the first characteristic variable and the second characteristic variable.

The method for acquiring the second characteristic variable is the same as the method for acquiring the first characteristic variable, and is described in detail later. The account data having the association relationship and the plurality of other account data are friend relationships, and it can be understood that the plurality of other account data are friends of the account data. Both the online behavior and the offline behavior in the above example can be mapped to the behavior of a certain application account through a certain correspondence. For example, the navigation service and the instant messaging application are registered by the other account data by using the mobile phone number, and when behavior data of the other account data is acquired, behavior data of the other account data in the navigation service and behavior data of the other account data in the instant messaging application are acquired.

Inputting the first characteristic variable and the second characteristic variable to the data analysis model includes: acquiring intimacy between a plurality of other account data and the account data, wherein the intimacy is generated according to the interaction behavior of each other account data and the account data; and acquiring a third characteristic variable according to the intimacy degree and the second characteristic variable by adopting the following formula:

υ'＝f((α₁,α₂,...,α_i,...,α_n),(υ₁,υ₂,...,υ_i,...,υ_n))，

where υ' represents a third feature variable, i represents the ith other account number data, α_iIs the intimacy, upsilon, of the ith other account data and the account data_iF is a weighted average value of the second characteristic variables of the first n other account data and the intimacy degree in the sequence from high intimacy degree to low intimacy degree; the first characteristic variable and the third characteristic variable are input to a data analysis model.

In this embodiment, the second characteristic variables of other account data are subjected to data processing, so that the behavior characteristics of the account data can be better reflected. Therefore, when the second variables are obtained, each second feature variable is multiplied by a corresponding weight value, and then weighted average is performed. The weight value represents the intimacy of the account data with other account data. The closer the account data and other account data are, the larger the weight value is; conversely, the smaller the weight value. Affinity may be measured by interactions between account data and other account data, such as the more chats between account data and other account data, the more intimate the relationship. The higher the community coincidence degree of the account data with other account data, the more intimate the relationship between the two account data is. The intimacy degree and the contact degree can be obtained by adopting a mode of training a model. The interactive behaviors include friend circle interactions, payment interactions (such as red bag), sport interactions (such as 1 ten thousand praise on foot), and the like. The intimacy can be embodied by the information interaction, including the times of sending and receiving information, the number of days and the like, the proportion of sending and receiving information, the number of times of information interaction every day and the like. The information includes text information, video information, voice information, and the like. Intimacy can also be obtained by commenting, praise, marking friends as special friends, giving gifts, or drawing black, etc.

For example, the third characteristic variable

That is, the intimacy degree is the weighted average of the second characteristic variables and the intimacy degrees of the first 10 friends arranged in the sequence from parent to sparse.

The general characteristics of a group can reflect the characteristics of a certain user in the group, so that the probability value that the behavior does not meet the preset condition can be obtained according to the characteristics of the group, and the credit degree of the user can be embodied more accurately. It should be noted that, when the second characteristic variables of the plurality of second accounts are obtained, n pieces of other account data before the intimacy ranking are selected according to the intimacy between friends of the account data and the account data, and then the third characteristic variable is generated according to the intimacy and the second characteristic variable.

Because the collected behavior data range is wider, the obtained data formats are different. Therefore, after behavior data are obtained, abnormal data are deleted, repeated data are removed, and data with large fluctuation values and missing data are compensated. Where the anomalous data may be data that is significantly out of range, for example, typically a person's age will not exceed one hundred, and if the collected data shows an age of 100, the anomalous data is deleted. If the collected data show that the ages include 0 and 49, 0 and 49 are in the range of 0 to 100, however, most of the other data are between 18 and 45, and therefore, 0 and 49 belong to singular points with large fluctuation values.

After the basic processing is performed on the behavior data, the behavior data is divided into a plurality of dimensions according to the data source and the service characteristics. For example, basic information, social interaction, financial management and the like are classified and integrated and written into the database. When writing to the database, the data type and data structure may be defined first. For example, the type of the numeric value is int, and the type of the area name is a character string. Other forms are possible, not just examples.

Because the amount of the stored behavior data is huge and many data have correlation, the data needs to be screened to obtain more significant features to be input into a data analysis model.

a) In the basic attribute, the work of the public officer and the crowd is stable, the economic source is reliable, and the economic capability and repayment willingness of the user can be reflected;

b) users who often do not reply to messages in time in social interaction may be lazy and loose, and the characters of the users are prolonged;

c) the users who often purchase value-added services and shop online can reflect the economic capability of the users;

d) stock, fund, P2P purchases in economic behavior may reflect the risk tolerance and economic ability of the user;

e) the reputation of the user can be reflected by making a special car and frequently canceling orders or having low evaluation star;

f) if the friends who the user often comes and goes are high in quality, the user is conservative and can feed back the user to a certain extent.

The basic attributes, the social interaction behaviors, the purchasing behaviors, the taxi taking behaviors and the friend attributes can all reflect the behavior characteristics of account data.

That is, as an embodiment, the obtaining of the first characteristic variable of the account data according to the behavior data includes: acquiring information gain of features in the behavior data, wherein the information gain is used for expressing the information quantity contained in the behavior data; judging whether the information gain is within a preset numerical range or not; if the information gain is within a preset numerical range, constructing a derivative variable according to the behavior data, wherein the derivative variable is the merged or split behavior data; if the information gain is out of the preset numerical range, deleting the characteristics corresponding to the information gain out of the preset numerical range, and constructing derivative variables according to the remaining characteristics; the derived variable is taken as the first characteristic variable.

As an embodiment, deleting the feature corresponding to the information gain outside the preset numerical range, and constructing the derivative variable according to the remaining features includes: after deleting the features corresponding to the information gains outside the preset numerical range, acquiring the correlation coefficients of the rest features; combining the features of which the relation number is greater than or equal to a preset coefficient into a combined feature; the merged features are used as derived variables.

The features and feature values constitute behavior data. For example, the collected behavior data includes the number of text chatting, the number of voice calls, the payment amount, etc., which are all features in the behavior data. And for example, 9 text chats, 10 voice calls, and a payment amount of 100, wherein the numbers are all called feature values. The information gain may represent a characteristic amount of information. If the amount of information is less than the threshold, the feature may be deleted. For example, the information gain is sorted for each type of feature, and features with information gains less than a threshold are deleted. Then, the correlation of the rest features is detected, and if the features with stronger correlation exist, the features with stronger correlation are combined to obtain a first feature variable. If a feature is strongly significant with weak correlation, the feature can be refined into multiple features. For example, the number of chats is divided into the number of night chats, the number of day chats, the number of weekend chats, the number of weekday chats, and the like. Conversely, the number of night chats and the number of day chats may be combined into the number of chats.

In this embodiment, the behavior data can be flexibly split and merged to construct the first feature variable, and during splitting and merging, the same or different methods can be used for a plurality of features (for example, a principal component analysis method is used for some features and a clustering method is used for other features), so that the flexibility of constructing the first feature variable is increased.

As an embodiment, before inputting the first characteristic variable and the second characteristic variable to the data analysis model, the method further comprises: dividing the behavioral data into a plurality of categories; respectively establishing a sub-model for each category in a plurality of categories, wherein each sub-model is used for outputting a first sub-value according to a first characteristic variable and/or a second characteristic variable, and the first sub-value is used for indicating a probability value that the behavior of the account data does not meet a preset condition under the category corresponding to the sub-model; and constructing a plurality of sub models corresponding to the plurality of categories into a data analysis model.

Specifically, when the data analysis model is established, that is, before the first characteristic variable and the second characteristic variable are input to the data analysis model, each category may be correspondingly generated into a sub-model according to the categories divided when behavior data are collected, each sub-model may output a first sub-value, and the first sub-values are processed to obtain a first numerical value output by the data analysis model. Further, when the submodel is established, training can be performed according to sample data of each category to obtain the submodel, or each category can be further divided, a low-level model is established for the divided data, the plurality of low-level models form the submodel, and then the submodel forms the data analysis model.

As an embodiment, the establishing a sub-model for each of the plurality of categories respectively comprises: respectively establishing a sub-model for each category by adopting the same or different training models; or respectively establishing a low-level model for the sub-categories under each category by adopting the same or different training models, and establishing the low-level models corresponding to the sub-categories under each category as sub-models.

The training models used for establishing the submodels for each category may be the same or different, for example, of 10 categories, 5 categories use decision tree training models, and the other 5 categories use neural network training submodels.

Optionally, constructing a plurality of sub-models corresponding to the plurality of categories as the data analysis model includes: constructing a plurality of sub-models into a data analysis model by adopting the following modes:

wherein, P_{General assembly}Representing a first value, i being the ith sub-model of the plurality of sub-models, n being the number of the plurality of sub-models,

is the coefficient of the ith sub-model, P_i' first sub-value, P, output for ith sub-model₀Is a constant feature.

Wherein dividing the behavior data into a plurality of categories comprises: dividing the behavior data into a plurality of categories according to the service types included in the behavior data; or the data including the target object in the behavior data is divided into one type, and the data not including the target object in the behavior data is divided into another type.

The three division methods can adopt any one of the three methods to independently construct the submodel or the combination of any two or three methods to construct the submodel according to the hierarchy division, the division according to the service type and the division whether the target object is included. For example, a sub-model is first established according to a partition that includes or does not include a target object, and then a low-level sub-model below the sub-model is divided according to a service type, and so on.

The sub-services are mainly classified by referring to the previous data categories, such as basic information, value-added services, social interaction, economic behaviors and the like; the grouping is mainly divided according to the business characteristics, for example, in the economic behavior, the behavior of the users with credit cards and without credit cards in payment, shopping, financing and the like has larger difference, so that the users can be divided into two groups and respectively build models; the layering is mainly expressed on the layering of the whole model architecture, such as a sub-model layer, the sub-model can also be divided into a plurality of dimension layers, and the machine learning algorithm adopted by each layer can be completely different.

In this embodiment, the steps 404 to 405 respectively correspond to the steps 301 to 302 in the foregoing embodiment, and therefore, a person skilled in the art can understand the steps 404 to 405 with reference to the foregoing embodiment, and details are not described herein for brevity.

By adopting the technical scheme of the embodiment of the invention, on one hand, accurate acquisition of user credit data is realized; on the other hand, under the condition that the first application client requests to access the second application client by using the account data of the first application client, the server sends the user credit data corresponding to the account data to the second application client, so that the second application client can execute corresponding service logic based on the user credit data, the corresponding service is provided based on the probability condition violating the preset rule, the probability of occurrence of safety problems such as information leakage or attack on a service platform and the like caused by a user with high probability of not complying with the preset rule in the service obtaining process is reduced, and the safety and reliability of service provision and the service platform are improved.

The embodiment of the invention also provides an information processing method. FIG. 5 is a third flowchart illustrating an information processing method according to an embodiment of the invention; as shown in fig. 5, the method includes:

step 501: based on a request for accessing a second application client by using account data of a first application client, a terminal obtains user credit data corresponding to the account data of the first application client, wherein the user credit data is used for representing the probability that a terminal user corresponding to the user identity mark violates a predetermined rule.

Step 502: and based on the user credit data, the terminal executes corresponding service logic through the second application client.

In this embodiment, the information processing method is applied to a terminal, and the terminal may specifically be a terminal device running a second application client, and may also be a terminal device capable of running a first application client and a second application client.

In an embodiment of the present invention, the accessing a second application client based on account data of a first application client, where the obtaining, by the terminal, user credit data corresponding to the account data of the first application client includes: requesting to access a second application client by account data of the first application client based on the terminal or another terminal, wherein the terminal requests and obtains a temporary identifier from a server through the second application client, and outputs identifier information comprising the temporary identifier; the server is a server corresponding to the first application client; and based on the terminal or the other terminal reading and identifying the identification information through the first application client, and based on the terminal or the other terminal requesting the server to access the second application client by the account data of the first application client, the terminal obtains the user credit data corresponding to the account data from the server through the second application client. The identification information is a graphic code, such as a two-dimensional code, a bar code, and the like.

In practical applications, for example, when a terminal can run a first application client and a second application client, after the terminal activates the second application client, the terminal can access the second application client by using account data of the first application client through detecting an input operation request for an identifier of the first application client in a display interface of the second application client, that is, the terminal sends a login request message to the second application client through an interface between the first application client and the second application client, and accesses a login request of the second application client by using the account data of the first application client; the displayed identifier of the first application client may specifically be a displayed icon or link of the first application client, and the user triggers the icon or link to request access to the corresponding second application client by using the account data of the first application client.

After receiving the login request message, the second application client communicates with a server (i.e., a server to which the first application client belongs) to obtain a temporary identifier, where the temporary identifier may be a UUID; as an implementation manner, the second application client may encode the temporary identifier in an encoding manner to generate identifier information, and display the identifier information through a display component of the terminal; the first application client identifies the identification information and obtains a temporary identification included by the identification information; the second application client can encode the temporary identifier in a two-dimensional code encoding mode to generate two-dimensional code information, and the terminal can display the two-dimensional code information through the display assembly; the first application client can recognize the two-dimension code information in an OCR mode, so that the temporary identifier carried by the two-dimension code information is obtained. The terminal sends a first message to the server through the first application to the client, wherein the first message comprises a user identity corresponding to account data of the first application client, and also comprises the temporary identifier and an application identifier (the application identifier is an application identifier corresponding to the second application client), so that the server can conveniently return authorization information to the second application client of the terminal, obtain corresponding user credit data according to the user identity, and return the user credit data to the second application client of the second terminal.

In this embodiment, the terminal obtains, from a server (specifically, a server to which the first application client belongs), user credit data corresponding to account data of the first application client, where the user credit data is used to characterize a probability that a terminal user corresponding to a user identity corresponding to the account data violates a predetermined rule. Wherein the user credit data may comprise at least one of the following data types: credit score, credit rating. In one embodiment, a higher credit score or credit rating indicates a lower probability that the corresponding end user violates the agreed upon rule, and a lower credit score or credit rating indicates a higher probability that the corresponding end user violates the agreed upon rule. Here, violations of the predetermined rules include two broad categories: the first type, the user is requested to actively execute a certain violation operation and the like as a default, for example, a movie without copyright is clicked in an application; in the second category, the user does not perform obligations defined by the predetermined rules, e.g., the user is overdue and not paid for, etc., as a default.

In this embodiment, the credit score may be a composite score based on various data such as historical behavior data of the user using the service, or may be an initial score based on personal attributes, or may be a single credit score based on a current application scenario sent when the service request is sent.

In this embodiment, as an implementation manner, when the terminal or another terminal confirms authorization to access the second application client by using the account data of the first application client through the first application client, a notification message is sent to the server, and based on the notification message, the terminal obtains, through the second application client, the user credit data associated with the account data returned by the server. As another embodiment, the terminal or another terminal confirms the request to access the second application client by the account data of the first application client through the first application client, that is, the terminal or another terminal sends a notification message to the server after obtaining the temporary identifier through the first application client, and based on the notification message, the terminal obtains the user credit data associated with the account data from the server through the second application client.

In this embodiment, the terminal executes, by the second application client, a corresponding service logic based on the user credit data, where the service logic is an operation executed in response to the access request and/or an operation sequence. For example, if the credit score of the user a is low and is a default user with a high probability, the terminal may execute the blocking logic through the second application client, and when the blocking logic is executed, the second application client may not respond to the access request of the user, and further may output notification information indicating that the service is not provided. For example, if the credit score of the user B is high and is a low probability user violating the predetermined rule, the second application client directly responds to the access request of the user B based on the account data of the first application client to provide the user B with the required service.

As an embodiment, the method further comprises: obtaining a user label of account data according to the user credit data and label distribution logic, wherein the user label is used for representing the available service range of the account data; the user tag at least comprises: the first type of user tags are used for indicating users of which the probability that the terminal users corresponding to the account data violate the predetermined rule is within a first range; the second type of user tag is used for indicating that the probability that the terminal user corresponding to the account data violates the predetermined rule is within a second range, wherein the first range is different from the second range; the executing, based on the user credit data, the respective service logic of the second application client corresponding to the requested access includes at least one of: executing service logic corresponding to the first class of user tags, and shielding access requests or partial response access requests aiming at the second application client; and executing service logic corresponding to the second type of user tags, and partially or totally responding to the access request aiming at the second application client.

In this embodiment, the terminal will give the user tag of the current access request according to the user credit data and the tag distribution logic through the second application client. The label distribution logic is a decision rule that assigns user labels to users based on user credit data. For example, the label distribution logic may include a mapping table, where the mapping table includes a correspondence between user credit data and a corresponding user label, and the terminal may obtain, through the second application client, the corresponding user label based on the user credit data according to the correspondence. The user tags may include a variety of types, for example, the user tags may be: a conservative user and a non-conservative user. The conservative users may be assigned to users who do not comply with the predetermined rule by more than a predetermined threshold, and the non-conservative users may be assigned to users who do not comply with the predetermined rule by more than a predetermined threshold. In some embodiments each of the user tags may be further divided into a plurality of sub-categories of user tags. For example, taking a ticket purchase as an example, the user tags that may be generated according to the credit score may include: the system comprises a plurality of general users, wherein the general users comprise cattle, a first class of general users and a second class of general users. The "cattle (cattle refers to a part of people who buy goods or ticket vouchers and sell the goods or ticket vouchers at high price in a charm)" has the lowest credit score and the highest probability of violating the predetermined rule. The credit corresponding to the first type of common users is low in grade, and the default behaviors such as ticket passing and returning exist. The 'second class of common users' have the highest credit score and never generate the behavior of returning tickets. In this embodiment, the "cattle" and the "first-class common users" may be subclass user tags of the first-class user tags; the second type common user is a subclass user label of the second type user label. In some embodiments the user tag may further comprise: a vouching user; the vouching user may be a user who has prepaid a wager, such as a premium, and who is provided with a wager if the user of that category violates a default, the user of that category may have a high credit score, and then another sub-category of the second category of user tags.

Wherein the user tag comprises at least: a first class of user tags and a second class of user tags, wherein the first class of user tags is used for indicating users whose probability that the requesting user violates the predetermined rule is within a first range; the second class of user tags is used to indicate users whose probability of the requesting user violating the predetermined rule is within a second range, wherein the first range is different from the second range. In this embodiment, the user tags at least include a first type of user tags and a second type of user tags. The first category of user tags here may be users who have a very high probability of not complying with the predetermined rule. The second class of users are users that comply with the predetermined rule. In the embodiment, users are divided into two categories, and in a specific implementation process, the users may not be limited to the two categories.

In this embodiment, once the user tag is determined, the terminal may execute the service logic corresponding to the user tag through the second application client. For example, services may be provided normally for conservative users, while no services or only partial services may be provided for non-conservative users.

As an implementation manner, the terminal executes the service logic corresponding to the first class of user tags through the second application client, and masks the service request or partially responds to the service request. If the user tag of the current requesting user is the first class user tag, the service request of the user can be shielded, and the second application client of the terminal does not provide service for the requesting user, then the service range obtained by the user is zero at this moment. Partially responding to the service request, in order to not completely respond to the service required by the service request, for example, a user whose user tag is a first type of user tag requests to query information of other users, where the information requested to query includes sensitive information and non-sensitive information, where partially responding to the service request may include: only the inquiry requests of the non-sensitive information are responded, and the inquiry requests of the sensitive information are shielded.

As another implementation, the terminal executes the service logic corresponding to the second type of user tag through the second application client, and responds to the service request partially or completely.

By adopting the technical scheme of the embodiment of the invention, under the condition that the account data of the first application client requests to access the second application client, the server sends the user credit data corresponding to the account data to the second application client of the terminal, so that the second application client of the terminal can execute corresponding service logic based on the user credit data, the terminal can provide corresponding service based on the probability condition violating the preset rule, the probability of safety problems such as information leakage or attack on a service platform and the like caused by users with high probability of not complying with the preset rule in the process of obtaining the service is reduced, and the safety and reliability of service provision and the service platform are improved.

The embodiment of the invention also provides an information processing method. The method comprises the following steps:

step 1: based on a request for accessing a second application client with account data of the first application client, a server obtains a first message from a first terminal including the first application client; the first message includes a user identity corresponding to account data of the first application client.

Step 2: the server obtains user credit data associated with the user identity and sends the user credit data to a second terminal comprising the second application client; the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

And step 3: and based on the user credit data, the second terminal executes corresponding service logic through the second application client.

The above steps of this embodiment can refer to the description in the foregoing embodiments, and are not described herein again.

The information processing method according to the embodiment of the present invention is described below with reference to specific application scenarios. FIG. 6a and FIG. 6b are schematic interaction flow diagrams of an information processing method according to an embodiment of the present invention; as a first interaction means, as shown in fig. 6a, the method includes:

step 601: and the main application client sends a login request to the third-party application client, wherein the login request is specifically used for requesting to login the third-party application client by using the account of the main application client. The login request includes a user identity, which may be a unique UID corresponding to an account of the primary application client.

Step 602: the third party application client requests a temporary identifier from a main application server corresponding to the main application client based on the login request of the main application client, wherein the temporary identifier can be a temporary UUID, and the temporary UUID is only effective for the request; or the temporary UUID is valid for a preset time frame (e.g., five minutes). Wherein, the request message may include the user identity of the primary application client; the temporary identifier generated by the primary application server corresponds to the user identity of the primary application client.

Step 603: and the main application server returns the temporary identifier to the third-party application client.

Step 604: and the third party application client generates a graphic code based on the temporary identifier and an application identifier (APP ID), displays the graphic code, wherein the graphic code can be a two-dimensional code, and then the third party application client generates and displays the two-dimensional code according to the obtained temporary UUID and the application identifier code of the third party application client.

Step 605: the third-party application client side polls the main application server to obtain information whether the user confirms login, wherein the information carries a temporary identifier; step 604 and step 605 do not differ in sequence, and may be performed first in step 604 and then in step 605, or may be performed first in step 605 and then in step 604, or may be performed in step 604 and step 605 at the same time, where the execution sequence is not limited in this embodiment.

Step 606 to step 607: and the main application client scans the graphic code displayed by the third-party application client to obtain the temporary identifier and the application identifier carried by the graphic code. The main application client has a graphic code scanning and reading function, and after the function is activated, as an implementation mode, an image containing identification information is obtained by calling a camera, and a temporary identification and an application identification carried by a graphic code in the image are further identified. For example, the main application client starts a graphic code scanning function and calls a camera to enable the main application client to display a display interface comprising a scanning frame; when the camera collects image data so that the collected graphic code is in the scanning frame, the main application client scans the collected graphic code based on the graphic code scanning function to obtain a temporary identifier and an application identifier carried by the graphic code. As another implementation, the primary application client has an OCR function, that is, directly recognizes characters in an image containing a graphic code, and further obtains a temporary identifier and an application identifier carried by the graphic code based on the recognized characters.

Step 608: and the main application client informs the main application server, the notification is used for requesting to log in the third-party application by using the account number of the main application client, the notification message carries the temporary identifier, the user identity identifier and the application identifier which are obtained by scanning, and the application identifier is the identifier of the third-party application client.

Step 609: the main application server returns authorization information to the third-party application client based on the notification message, and carries an access token (access token).

Step 610: the third party application client requests confirmation authorization from the master application client. In practical applications, the display interface based on the client of the main application can display, for example, "authorization" and "unauthorized" virtual keys, so that the user can confirm authorization by clicking the "authorization" virtual key or confirm unauthorized by clicking the "unauthorized" virtual key.

Step 611: and the main application client confirms the authorization to the third-party application client, namely, the user clicks an authorization virtual key to determine that the main application client confirms the authorization to the third-party application client, and the third-party application client allows the user to log in by using the account of the main application client.

Step 612: after the authorization is confirmed, the third-party application client requests the main application server to obtain user information, the request comprises information such as temporary identification, an access token and application identification, the main application server can determine the user identity identification of the corresponding main application client based on the temporary identification in the request, obtains the user information corresponding to the user identity identification based on the user identity identification, and returns the user information to the third-party application client.

Step 613: and the primary application client logs in the third-party application client by using the account of the primary application client.

Step 614: the third-party application client requests the user credit data from the main application server, and the request can comprise information such as temporary identification, access token, application identification and the like.

Step 615: the primary application server determines a user identity of the corresponding primary application client based on the temporary identity in the request, and obtains corresponding user credit data, such as a user credit rating and/or a user credit score, based on the user identity. Further, the main application server may perform identification and judgment based on the user credit data, and determine whether the user credit data represents that the probability that the end user corresponding to the user identity violates the predetermined rule is higher, for example, the probability that the end user corresponding to the user credit data with a lower score or a lower rank violates the predetermined rule is higher; when the probability that the terminal user corresponding to the user identity identification is violated by the user credit data representation is judged to be higher, the main application server can generate prompt information, the probability that the terminal user is violated by the prompt information representation is higher, and the service providing has certain risks.

Step 616: the main application server sends the user credit data to the third-party application client so that the third-party application client executes corresponding logic based on the user credit data; or the main application server sends prompt information to the third-party application client, the prompt information represents that the probability that the terminal user violates the predetermined rule is high, and the service provision has certain risks.

Step 617: the third party application client performs corresponding service logic based on the user credit data, for example, responding to the access request in whole or in part, or masking the access request. Or the third-party application client shields the access request based on the received prompt information or partially responds to the access request.

As another interaction manner, as shown in fig. 6b, step 601 to step 608 may refer to the related description in fig. 6a, which is not described herein again, and after step 608, the method further includes:

step 609': the primary application server determines the user id of the corresponding primary application client based on the temporary identifier carried in the notification request of step 608, and obtains corresponding user credit data based on the user id, for example, the user credit rating and/or the user credit score. Further, the main application server may perform identification and judgment based on the user credit data, and determine whether the user credit data represents that the probability that the end user corresponding to the user identity violates the predetermined rule is higher, for example, the probability that the end user corresponding to the user credit data with a lower score or a lower rank violates the predetermined rule is higher; when the probability that the terminal user corresponding to the user identity identification is violated by the user credit data representation is judged to be higher, the main application server can generate prompt information, the probability that the terminal user is violated by the prompt information representation is higher, and the service providing has certain risks.

Step 610': the main application server returns authorization information and an access token (access token) to the third-party application client based on the notification message, and carries user credit data or prompt information representing that the credit is low.

Step 611': the third party application client requests confirmation authorization from the master application client. In practical applications, the display interface based on the client of the main application can display, for example, "authorization" and "unauthorized" virtual keys, so that the user can confirm authorization by clicking the "authorization" virtual key or confirm unauthorized by clicking the "unauthorized" virtual key.

Step 612': and the main application client confirms the authorization to the third-party application client, namely, the user clicks an authorization virtual key to determine that the main application client confirms the authorization to the third-party application client, and the third-party application client allows the user to log in by using the account of the main application client.

Step 613': after the authorization is confirmed, the third-party application client requests the main application server to obtain user information, the request comprises information such as temporary identification, an access token and application identification, the main application server can determine the user identity identification of the corresponding main application client based on the temporary identification in the request, obtains the user information corresponding to the user identity identification based on the user identity identification, and returns the user information to the third-party application client.

Step 614': and the primary application client logs in the third-party application client by using the account of the primary application client.

Step 615': the third party application client performs corresponding service logic based on the user credit data, for example, responding to the access request in whole or in part, or masking the access request. Or the third-party application client shields the access request based on the received prompt information or partially responds to the access request.

The embodiment of the invention also provides a server. Fig. 7 is a schematic structural diagram of a server according to an embodiment of the present invention, and as shown in fig. 7, the server includes: a first communication unit 71, a first acquisition unit 72, and a second communication unit 73; the first communication unit 71 is configured to request to access a second application client based on account data of a first application client, and obtain a first message from a first terminal including the first application client; the first message comprises a user identity corresponding to the account data of the first application client; the first obtaining unit 72 is configured to obtain user credit data associated with the user identity; the user credit data is used for representing the probability that the terminal user corresponding to the user identity label violates a preset rule; the second communication unit 73 is configured to send the user credit data obtained by the first obtaining unit 72 to a second terminal including the second application client, so that the second application client of the second terminal executes a corresponding service logic based on the user credit data.

In an embodiment, the second communication unit 73 is configured to send the user credit data to the second application client in response to a confirmation message obtained characterizing that the second application client is authorized to access with the account data of the first application client.

In an embodiment, the first communication unit 71 is configured to obtain a first message from the first terminal based on the first terminal reading, through the first application client, identification information identifying that the second terminal outputs through the second application client, where the first message includes the user identity and the assigned temporary identifier.

As an implementation manner, fig. 8 is a schematic diagram of another composition structure of the server according to the embodiment of the present invention, and as shown in fig. 8, the server further includes a collecting unit 74 and a second obtaining unit 75; the acquiring unit 74 is configured to acquire behavior data corresponding to the account data, where the behavior data includes internet-based online behavior data and internet-based offline behavior data; the second obtaining unit 75 is configured to obtain a first characteristic variable of the account data according to the behavior data collected by the collecting unit 74, where the first characteristic variable is used to represent a behavior characteristic of the account data; inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable.

In this embodiment, the second obtaining unit 75 is configured to obtain a second characteristic variable, where the second characteristic variable is used to represent behavior characteristics of a plurality of other account data having an association relationship with the account data; inputting the first characteristic variable and the second characteristic variable into the data analysis model, wherein the data analysis model is further configured to output the user credit data according to the first characteristic variable and the second characteristic variable.

In this embodiment, the second obtaining unit 75 is configured to divide the behavior data into a plurality of categories; respectively establishing a sub-model for each category in the categories, wherein each sub-model is used for outputting a first sub-value according to the first characteristic variable and/or the second characteristic variable, and the first sub-value is used for indicating a probability value that the behavior of the account data does not meet the preset condition under the category corresponding to the sub-model; and constructing a plurality of sub models corresponding to the plurality of categories as the data analysis model.

In the embodiment of the present invention, the first obtaining Unit 72, the collecting Unit 74, and the second obtaining Unit 75 in the server may be implemented by a Central Processing Unit (CPU), a Digital Signal Processor (DSP), a Micro Control Unit (MCU) or a Programmable Gate Array (FPGA) in the server in practical application; the first communication unit 71 and the second communication unit 73 in the server can be implemented by a communication module (including a basic communication suite, an operating system, a communication module, a standardized interface, a protocol, and the like) and a transceiver antenna in practical application.

It should be noted that: in the above embodiment, when the server performs information processing, only the division of each program module is described as an example, and in practical applications, the processing may be distributed to different program modules according to needs, that is, the internal structure of the server may be divided into different program modules to complete all or part of the processing described above. In addition, the server and the information processing method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments for details, which are not described herein again.

The embodiment of the invention also provides the terminal. Fig. 9 is a schematic structural diagram of a terminal according to an embodiment of the present invention, and as shown in fig. 9, the terminal includes: a third communication unit 81 and an execution unit 82; the third communication unit 81 is configured to access a second application client based on account data of a first application client, and obtain user credit data corresponding to the account data of the first application client, where the user credit data is used to represent a probability that an end user corresponding to the user identity identifier violates a predetermined rule; the executing unit 82 is configured to execute a corresponding service logic through the second application client based on the user credit data obtained by the third communicating unit 81.

In an embodiment, the execution unit 82 is further configured to obtain a user tag of the account data according to the user credit data and a tag distribution logic, where the user tag is used to characterize an available service range of the account data; the user tag at least comprises: the first type of user tags are used for indicating users of which the probability that the terminal users corresponding to the account data violate the predetermined rule is within a first range; the second type of user tag is used for indicating that the probability that the terminal user corresponding to the account data violates the predetermined rule is within a second range, wherein the first range is different from the second range; further configured to execute respective service logic based on the user credit data, including at least one of: executing service logic corresponding to the first class of user tags, and shielding access requests or partially responding to the access requests; and executing service logic corresponding to the second type of user tags, and responding to the access request partially or completely.

In an embodiment, the terminal further comprises an output unit; the third communication unit 81 is configured to access a second application client by using the account data of the first application client based on the request of the terminal or another terminal, and request and obtain a temporary identifier from a server through the second application client; the server is a server corresponding to the first application client; the output unit is configured to output identification information including the temporary identification; the third communication unit 81 is further configured to, based on the terminal or the another terminal reading and recognizing the identification information through the first application client, and based on the terminal or the another terminal requesting the server to access the second application client with the account data of the first application client, obtain, through the second application client, user credit data corresponding to the account data from the server.

In the embodiment of the present invention, the execution unit 82 in the terminal may be implemented by a CPU, a DSP, an MCU, or an FPGA in the terminal in practical application; the third communication unit 81 in the terminal can be implemented by a communication module (including a basic communication suite, an operating system, a communication module, a standardized interface, a protocol and the like) and a transceiving antenna in practical application; the output unit in the terminal can be realized through a display component of the terminal in practical application.

It should be noted that: in the terminal provided in the above embodiment, when performing information processing, only the division of each program module is exemplified, and in practical applications, the processing distribution may be completed by different program modules according to needs, that is, the internal structure of the terminal is divided into different program modules to complete all or part of the processing described above. In addition, the terminal and the information processing method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments for details, which are not described herein again.

Fig. 10 is a schematic diagram of a hardware structure of the server according to the embodiment of the present invention; as shown in fig. 10, includes a memory 92, a processor 91, and a computer program stored on the memory 92 and executable on the processor 91, and further includes a power component and a communication component 93, each coupled together by a bus system 94. It will be appreciated that the bus system 94 is used to enable communications among the components. The bus system 94 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 94 in fig. 10.

It will be appreciated that the memory 92 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The memory 92 described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.

The processor 91 may be an integrated circuit chip having signal processing capability. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 91. The processor 91 described above may be a general purpose processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 91 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in memory 92, and the processor 91 reads the information in memory 92 and performs the steps of the aforementioned methods in conjunction with its hardware.

In this embodiment, the processor 91 implements, when executing the program,: accessing a second application client based on account data of a first application client, and obtaining a first message from a first terminal comprising the first application client; the first message comprises a user identity corresponding to the account data of the first application client; obtaining user credit data associated with the user identity, and sending the user credit data to a second terminal comprising the second application client so as to enable the second application client of the second terminal to execute corresponding service logic based on the user credit data; the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

As an embodiment, the processor 91, when executing the program, implements: sending the user credit data to the second application client in response to an acknowledgement message obtained characterizing authorization to access the second application client with account data of the first application client.

As an embodiment, the processor 91, when executing the program, implements: and obtaining a first message from the first terminal based on the first terminal reading and identifying the identification information output by the second terminal through the second application client through the first application client, wherein the first message comprises the user identity identification and the allocated temporary identification.

As an embodiment, the processor 91, when executing the program, further implements: acquiring behavior data corresponding to the account data, wherein the behavior data comprises online behavior data and offline behavior data based on the Internet; acquiring a first characteristic variable of the account data according to the behavior data, wherein the first characteristic variable is used for representing the behavior characteristic of the account data; inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable.

As an embodiment, the processor 91, when executing the program, further implements: acquiring a second characteristic variable, wherein the second characteristic variable is used for representing behavior characteristics of a plurality of other account data having an association relationship with the account data; inputting the first characteristic variable and the second characteristic variable into the data analysis model, wherein the data analysis model is further configured to output the user credit data according to the first characteristic variable and the second characteristic variable.

As an embodiment, the processor 91, when executing the program, further implements: dividing the behavioral data into a plurality of categories; respectively establishing a sub-model for each category in the categories, wherein each sub-model is used for outputting a first sub-value according to the first characteristic variable and/or the second characteristic variable, and the first sub-value is used for indicating a probability value that the behavior of the account data does not meet the preset condition under the category corresponding to the sub-model; and constructing a plurality of sub models corresponding to the plurality of categories as the data analysis model.

Fig. 11 is a schematic diagram of a combination of hardware and software of the terminal according to the embodiment of the present invention, as shown in fig. 11, including a memory 802, a processor 801, a computer program stored in the memory 802 and capable of running on the processor 801, and at least one network interface 804 and a user interface 803, where the components are coupled together by a bus system 805. It is understood that the bus system 805 is used to enable communications among the components connected. The bus system 805 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 805 in FIG. 11.

Unlike the aforementioned server shown in fig. 10, the memory 802 in the present embodiment is also used to store various types of data to support the operation of the terminal. Examples of such data include: any computer programs for operation on the terminal, such as operating system 8021 and application programs 8022, contact data, phonebook data, messages, pictures, videos, and the like. Operating system 8021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application 8022 may contain various applications such as a media player (MediaPlayer), a Browser (Browser), and the like for implementing various application services. A program implementing a method according to an embodiment of the present invention may be included in application program 8022.

In this embodiment, when the processor 801 executes the program, it implements: based on a request for accessing a second application client by account number data of a first application client, obtaining user credit data corresponding to the account number data of the first application client, wherein the user credit data is used for representing the probability that an end user corresponding to the user identity mark violates a predetermined rule; executing, by the second application client, corresponding service logic based on the user credit data.

As an embodiment, the processor 801 executes the program to implement: obtaining a user label of the account data according to the user credit data and label distribution logic, wherein the user label is used for representing an available service range of the account data; the user tag at least comprises: the first type of user tags are used for indicating users of which the probability that the terminal users corresponding to the account data violate the predetermined rule is within a first range; the second type of user tag is used for indicating that the probability that the terminal user corresponding to the account data violates the predetermined rule is within a second range, wherein the first range is different from the second range; and executing, based on the user credit data, respective service logic of the second application client corresponding to the requested access, including at least one of: executing service logic corresponding to the first class of user tags, and shielding access requests or partial response access requests aiming at the second application client; and executing service logic corresponding to the second type of user tags, and partially or totally responding to the access request aiming at the second application client.

As an embodiment, the processor 801 executes the program to implement: requesting to access a second application client by account data of the first application client based on the terminal or another terminal, wherein the terminal requests and obtains a temporary identifier from a server through the second application client, and outputs identifier information comprising the temporary identifier; the server is a server corresponding to the first application client; and based on the terminal or the other terminal reading and identifying the identification information through the first application client, and based on the terminal or the other terminal requesting the server to access the second application client by the account data of the first application client, the terminal obtains the user credit data corresponding to the account data from the server through the second application client.

In an exemplary embodiment, the present invention further provides a computer storage medium, such as a memory 92 including a computer program shown in fig. 10, which is executable by a processor 91 of a server to perform the steps of the foregoing method. The computer storage medium can be FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disk, or CD-ROM; or may be various devices including one or any combination of the above memories.

The computer storage medium provided by the embodiment of the invention is stored with computer instructions, and the instructions are executed by a processor to realize that: accessing a second application client based on account data of a first application client, and obtaining a first message from a first terminal comprising the first application client; the first message comprises a user identity corresponding to the account data of the first application client; obtaining user credit data associated with the user identity, and sending the user credit data to a second terminal comprising the second application client so as to enable the second application client of the second terminal to execute corresponding service logic based on the user credit data; the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

As an embodiment, the instructions when executed by the processor implement: sending the user credit data to the second application client in response to an acknowledgement message obtained characterizing authorization to access the second application client with account data of the first application client.

As an embodiment, the instructions when executed by the processor implement: and obtaining a first message from the first terminal based on the first terminal reading and identifying the identification information output by the second terminal through the second application client through the first application client, wherein the first message comprises the user identity identification and the allocated temporary identification.

As an embodiment, the instructions when executed by the processor further implement: acquiring behavior data corresponding to the account data, wherein the behavior data comprises online behavior data and offline behavior data based on the Internet; acquiring a first characteristic variable of the account data according to the behavior data, wherein the first characteristic variable is used for representing the behavior characteristic of the account data; inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable.

As an embodiment, the instructions when executed by the processor further implement: acquiring a second characteristic variable, wherein the second characteristic variable is used for representing behavior characteristics of a plurality of other account data having an association relationship with the account data; inputting the first characteristic variable and the second characteristic variable into the data analysis model, wherein the data analysis model is further configured to output the user credit data according to the first characteristic variable and the second characteristic variable.

As an embodiment, the instructions when executed by the processor further implement: dividing the behavioral data into a plurality of categories; respectively establishing a sub-model for each category in the categories, wherein each sub-model is used for outputting a first sub-value according to the first characteristic variable and/or the second characteristic variable, and the first sub-value is used for indicating a probability value that the behavior of the account data does not meet the preset condition under the category corresponding to the sub-model; and constructing a plurality of sub models corresponding to the plurality of categories as the data analysis model.

Embodiments of the present invention further provide a computer storage medium, such as a memory 802 including a computer program shown in fig. 11, which can be executed by a processor 801 of a terminal to perform the steps of the foregoing method. The computer storage medium can be FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disk, or CD-ROM; or may be a variety of devices including one or any combination of the above memories, such as a mobile phone, computer, tablet device, personal digital assistant, etc.

The computer storage medium provided by the embodiment of the invention is stored with computer instructions, and the instructions are executed by a processor to realize that: based on a request for accessing a second application client by account number data of a first application client, obtaining user credit data corresponding to the account number data of the first application client, wherein the user credit data is used for representing the probability that an end user corresponding to the user identity mark violates a predetermined rule; executing, by the second application client, corresponding service logic based on the user credit data.

As an embodiment, the instructions when executed by the processor further implement: obtaining a user label of the account data according to the user credit data and label distribution logic, wherein the user label is used for representing an available service range of the account data; the user tag at least comprises: the first type of user tags are used for indicating users of which the probability that the terminal users corresponding to the account data violate the predetermined rule is within a first range; the second type of user tag is used for indicating that the probability that the terminal user corresponding to the account data violates the predetermined rule is within a second range, wherein the first range is different from the second range; and executing, based on the user credit data, respective service logic of the second application client corresponding to the requested access, including at least one of: executing service logic corresponding to the first class of user tags, and shielding access requests or partial response access requests aiming at the second application client; and executing service logic corresponding to the second type of user tags, and partially or totally responding to the access request aiming at the second application client.

As an embodiment, the instructions when executed by the processor further implement: requesting to access a second application client by account data of the first application client based on the terminal or another terminal, wherein the terminal requests and obtains a temporary identifier from a server through the second application client, and outputs identifier information comprising the temporary identifier; the server is a server corresponding to the first application client; and based on the terminal or the other terminal reading and identifying the identification information through the first application client, and based on the terminal or the other terminal requesting the server to access the second application client by the account data of the first application client, the terminal obtains the user credit data corresponding to the account data from the server through the second application client.

In an embodiment, the server is configured to send the user credit data to the second application client in response to a confirmation message obtained characterizing an authorization to access the second application client with account data of the first application client.

In an embodiment, the server is configured to obtain a first message from the first terminal based on the first terminal reading, through the first application client, identification information identifying that the second terminal outputs through the second application client, where the first message includes the user identity and a temporary identifier assigned by the server.

In an embodiment, the server is further configured to collect behavior data corresponding to the account data, where the behavior data includes internet-based online behavior data and internet-based offline behavior data; acquiring a first characteristic variable of the account data according to the behavior data, wherein the first characteristic variable is used for representing the behavior characteristic of the account data; inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable.

In an embodiment, the server is configured to obtain a second characteristic variable, where the second characteristic variable is used to represent behavior characteristics of a plurality of other account data having an association relationship with the account data; inputting the first characteristic variable and the second characteristic variable into the data analysis model, wherein the data analysis model is further configured to output the user credit data according to the first characteristic variable and the second characteristic variable.

In an embodiment, the server is configured to classify the behavior data into a plurality of categories before inputting the first characteristic variable and the second characteristic variable to the data analysis model; respectively establishing a sub-model for each category in the categories, wherein each sub-model is used for outputting a first sub-value according to the first characteristic variable and/or the second characteristic variable, and the first sub-value is used for indicating a probability value that the behavior of the account data does not meet the preset condition under the category corresponding to the sub-model; and constructing a plurality of sub models corresponding to the plurality of categories as the data analysis model.

In an embodiment, the terminal is further configured to obtain a user tag of the account data according to the user credit data and a tag distribution logic, where the user tag is used to characterize an available service range of the account data; the user tag at least comprises: the first type of user tags are used for indicating users of which the probability that the terminal users corresponding to the account data violate the predetermined rule is within a first range; the second type of user tag is used for indicating that the probability that the terminal user corresponding to the account data violates the predetermined rule is within a second range, wherein the first range is different from the second range; the executing, based on the user credit data, the respective service logic of the second application client corresponding to the requested access includes at least one of: executing service logic corresponding to the first class of user tags, and shielding access requests or partial response access requests aiming at the second application client; and executing service logic corresponding to the second type of user tags, and partially or totally responding to the access request aiming at the second application client.

In an embodiment, the terminal is further configured to access a second application client based on the account data of the first application client requested by the terminal or another terminal, and the terminal requests and obtains a temporary identifier from a server through the second application client and outputs identifier information including the temporary identifier; the server is a server corresponding to the first application client; and based on the terminal or the other terminal reading and identifying the identification information through the first application client, and based on the terminal or the other terminal requesting the server to access the second application client by the account data of the first application client, the terminal obtains the user credit data corresponding to the account data from the server through the second application client.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.

Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims

1. An information processing method, which is applied to a server to which a first application client belongs, includes:

acquiring behavior data corresponding to account data of the first application client, wherein the behavior data comprises internet-based online behavior data and internet-based offline behavior data;

acquiring a first characteristic variable of the account data according to the behavior data, wherein the first characteristic variable is used for representing the behavior characteristic of the account data;

inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable;

requesting to access a second application client based on account data of the first application client, and obtaining a first message from a first terminal comprising the first application client; the first message comprises a user identity corresponding to the account data of the first application client;

obtaining user credit data associated with the user identity, and sending the user credit data to a second terminal comprising the second application client so as to enable the second application client of the second terminal to execute corresponding service logic based on the user credit data;

the user credit data is used for representing the probability that the end user corresponding to the user identity mark violates the preset rule.

2. The method of claim 1, wherein the transmitting the user credit data to a second terminal comprising the second application client comprises:

sending the user credit data to the second application client in response to an acknowledgement message obtained characterizing authorization to access the second application client with account data of the first application client.

3. The method of claim 1, wherein the obtaining a first message from a first terminal comprising the first application client based on requesting access to a second application client with account data of the first application client comprises:

and obtaining a first message from the first terminal based on the first terminal reading and identifying the identification information output by the second terminal through the second application client through the first application client, wherein the first message comprises the user identity identification and the temporary identification distributed by the server.

4. The method of claim 1, wherein said inputting the first feature variable into a data analysis model comprises:

acquiring a second characteristic variable, wherein the second characteristic variable is used for representing behavior characteristics of a plurality of other account data having an association relationship with the account data;

inputting the first characteristic variable and the second characteristic variable into the data analysis model, wherein the data analysis model is further configured to output the user credit data according to the first characteristic variable and the second characteristic variable.

5. The method of claim 4, wherein prior to inputting the first and second characteristic variables to the data analysis model, the method further comprises:

dividing the behavioral data into a plurality of categories;

respectively establishing a sub-model for each category in the categories, wherein each sub-model is used for outputting a first sub-value according to the first characteristic variable and/or the second characteristic variable, and the first sub-value is used for indicating a probability value that the behavior of the account data does not meet a preset condition under the category corresponding to the sub-model;

and constructing a plurality of sub models corresponding to the plurality of categories as the data analysis model.

6. An information processing method applied to a terminal running a second application client, the method comprising:

based on the account data request of a first application client, accessing a second application client, and obtaining user credit data corresponding to the account data of the first application client, wherein the user credit data is used for representing the probability that an end user corresponding to the user identity mark violates a predetermined rule;

obtaining a user label of the account data according to the user credit data and label distribution logic, wherein the user label is used for representing an available service range of the account data;

the user tag at least comprises: the first type of user tags are used for indicating users of which the probability that the terminal users corresponding to the account data violate the predetermined rule is within a first range; the second type of user tag is used for indicating that the probability that the terminal user corresponding to the account data violates the predetermined rule is within a second range, wherein the first range is different from the second range;

executing service logic corresponding to the first class of user tags, and shielding access requests or partial response access requests aiming at the second application client; or executing service logic corresponding to the second type of user tags, and responding to the access request aiming at the second application client partially or completely.

7. The method of claim 6, wherein obtaining user credit data corresponding to account data of a first application client based on requesting access to a second application client with account data of the first application client comprises:

requesting to access a second application client by account data of the first application client based on the terminal or another terminal, wherein the terminal requests and obtains a temporary identifier from a server through the second application client, and outputs identifier information comprising the temporary identifier; the server is a server corresponding to the first application client;

and based on the terminal or the other terminal reading and identifying the identification information through the first application client, and based on the terminal or the other terminal requesting the server to access the second application client by the account data of the first application client, the terminal obtains the user credit data corresponding to the account data from the server through the second application client.

8. An information processing method, the method comprising:

the method comprises the steps that a server collects behavior data corresponding to account data of a first application client, wherein the behavior data comprise online behavior data and offline behavior data based on the Internet;

the server acquires a first characteristic variable of the account data according to the behavior data, wherein the first characteristic variable is used for representing the behavior characteristic of the account data;

the server inputs the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable;

based on requesting access to a second application client with account data of the first application client, the server obtaining a first message from a first terminal comprising the first application client; the first message comprises a user identity corresponding to account data of the first application client;

the server obtains user credit data associated with the user identity and sends the user credit data to a second terminal comprising the second application client; the user credit data is used for representing the probability that the terminal user corresponding to the user identity label violates a preset rule;

and based on the user credit data, the second terminal executes corresponding service logic through the second application client.

9. A server, the server comprising: the system comprises an acquisition unit, a second acquisition unit, a first communication unit, a first acquisition unit and a second communication unit;

the acquisition unit is configured to acquire behavior data corresponding to account data of the first application client, wherein the behavior data comprises internet-based online behavior data and internet-based offline behavior data;

the second obtaining unit is configured to obtain a first characteristic variable of the account data according to the behavior data collected by the collecting unit, wherein the first characteristic variable is used for representing a behavior characteristic of the account data; inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable;

the first communication unit is configured to request to access a second application client based on account data of a first application client, and obtain a first message from a first terminal including the first application client; the first message comprises a user identity corresponding to the account data of the first application client;

the first acquisition unit is configured to acquire user credit data associated with the user identity; the user credit data is used for representing the probability that the terminal user corresponding to the user identity label violates a preset rule;

the second communication unit is configured to send the user credit data obtained by the first obtaining unit to a second terminal including the second application client, so that the second application client of the second terminal executes corresponding service logic based on the user credit data.

10. The server according to claim 9, wherein the second communication unit is configured to send the user credit data to the second application client in response to a confirmation message obtained characterizing an authorization to access the second application client with account data of the first application client.

11. The server according to claim 9, wherein the first communication unit is configured to obtain a first message from the first terminal based on the first terminal reading, through the first application client, identification information identifying that the second terminal outputs through the second application client, and the first message includes the user identity and the assigned temporary identifier.

12. The server according to claim 9, wherein the second obtaining unit is configured to obtain a second characteristic variable, where the second characteristic variable is used to represent a behavior characteristic of a plurality of other account data having an association relationship with the account data; inputting the first characteristic variable and the second characteristic variable into the data analysis model, wherein the data analysis model is further configured to output the user credit data according to the first characteristic variable and the second characteristic variable.

13. The server according to claim 12, wherein the second obtaining unit is configured to divide the behavior data into a plurality of categories; respectively establishing a sub-model for each category in the categories, wherein each sub-model is used for outputting a first sub-value according to the first characteristic variable and/or the second characteristic variable, and the first sub-value is used for indicating a probability value that the behavior of the account data does not meet a preset condition under the category corresponding to the sub-model; and constructing a plurality of sub models corresponding to the plurality of categories as the data analysis model.

14. A terminal, the terminal comprising: a third communication unit and an execution unit;

the third communication unit is configured to access a second application client based on account data of a first application client, and obtain user credit data corresponding to the account data of the first application client, where the user credit data is used to represent a probability that an end user corresponding to the user identity identifier violates a predetermined rule;

the execution unit is configured to obtain a user tag of account data according to the user credit data and tag distribution logic, wherein the user tag is used for representing an available service range of the account data; the user tag at least comprises: the first type of user tags are used for indicating users of which the probability that the terminal users corresponding to the account data violate the predetermined rule is within a first range; the second type of user tag is used for indicating that the probability that the terminal user corresponding to the account data violates the predetermined rule is within a second range, wherein the first range is different from the second range;

the execution unit is further configured to execute the service logic corresponding to the first class of user tags, and shield the access request or partially respond to the access request; or executing service logic corresponding to the second type of user tags, and responding to the access request partially or completely.

15. The terminal of claim 14, wherein the terminal further comprises an output unit;

the third communication unit is configured to access a second application client by using the account data of the first application client based on the request of the terminal or another terminal, and request and obtain a temporary identifier from a server through the second application client; the server is a server corresponding to the first application client;

the output unit is configured to output identification information including the temporary identification;

the third communication unit is further configured to read and identify the identification information through the first application client based on the terminal or the other terminal, and obtain user credit data corresponding to the account data from the server through the second application client based on the terminal or the other terminal requesting the server to access the second application client with the account data of the first application client.

16. A computer storage medium having stored thereon computer instructions which, when executed by a processor, carry out the steps of the information processing method of any one of claims 1 to 5;

alternatively, the instructions, when executed by a processor, implement the steps of the information processing method of any one of claims 6 to 7.

17. A server comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the information processing method of any one of claims 1 to 5 when executing the program.

18. A terminal comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the information processing method of any one of claims 6 to 7 when executing the program.

19. An information processing system, the system comprising a server and a terminal;

the server is configured to collect behavior data corresponding to account data of the first application client, wherein the behavior data comprises internet-based online behavior data and internet-based offline behavior data; acquiring a first characteristic variable of the account data according to the behavior data, wherein the first characteristic variable is used for representing the behavior characteristic of the account data; inputting the first characteristic variable into a data analysis model to obtain user credit data; wherein the data analysis model is used for outputting user credit data according to the first characteristic variable;

the server is further configured to obtain a first message from the terminal or another terminal comprising the first application client based on a request for accessing a second application client with account data of the first application client; the first message comprises a user identity corresponding to account data of the first application client; obtaining user credit data associated with the user identity, and sending the user credit data to the terminal comprising the second application client; the user credit data is used for representing the probability that the terminal user corresponding to the user identity label violates a preset rule;

the terminal is configured to execute corresponding service logic through the second application client based on the user credit data.