WO2017041664A1 - 一种征信评分确定方法、装置及存储介质 - Google Patents

一种征信评分确定方法、装置及存储介质 Download PDF

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Publication number
WO2017041664A1
WO2017041664A1 PCT/CN2016/097791 CN2016097791W WO2017041664A1 WO 2017041664 A1 WO2017041664 A1 WO 2017041664A1 CN 2016097791 W CN2016097791 W CN 2016097791W WO 2017041664 A1 WO2017041664 A1 WO 2017041664A1
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Prior art keywords
user
credit score
score value
user group
users
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PCT/CN2016/097791
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English (en)
French (fr)
Inventor
卢铮
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腾讯科技（深圳）有限公司
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Publication of WO2017041664A1 publication Critical patent/WO2017041664A1/zh
Priority to US15/868,394 priority Critical patent/US20180137565A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/03—Credit; Loans; Processing thereof

Definitions

  • the present application relates to the field of Internet technologies, and in particular, to a method, an apparatus, and a storage medium for determining a credit score.
  • the personal credit score refers to the credit evaluation mechanism using the credit scoring model to quantify the personal credit information and express it in the form of scores.
  • the existing personal credit score calculation technology is mainly a bank personal credit information system, which uses the basic information of the user and the use record of the bank card and the credit card to calculate the personal credit score according to a certain calculation model.
  • the application provides a method, a device and a storage medium for determining a credit score.
  • an embodiment of the present application provides a method for determining a credit rating, including:
  • the user group includes a plurality of users having social relationships, and the plurality of users include the target users;
  • the current credit score value of the target user is determined as the credit score value of the target user.
  • the embodiment of the present application provides a credit score determining apparatus, including:
  • a user group obtaining unit configured to acquire a user group, where the user group includes multiple users having a social relationship, and the plurality of users include the target user;
  • a score update unit configured to determine, for each user in the user group, the current credit score value of the user after the last iteration update according to the user having a social relationship with the user, and iteratively update until the user The current credit score of each user in the user group satisfies the preset convergence result;
  • the score value determining unit is configured to determine the current credit score value of the target user as the credit score value of the target user.
  • the embodiment of the present application provides a credit score determining apparatus, including:
  • One or more processors configured to execute program instructions stored on the storage medium to cause the credit score determining means to perform:
  • the user group includes a plurality of users having social relationships, and the plurality of users include the target users;
  • the current credit score value of the target user is determined as the credit score value of the target user.
  • an embodiment of the present application provides a non-volatile computer readable storage medium, including program instructions, when the program instruction is executed by a processor, configuring the storage medium to execute:
  • the user group includes a plurality of users having social relationships, and the plurality of users include the target users;
  • the current credit score value of the target user is determined as the credit score value of the target user.
  • the method for determining the credit score provided by the embodiment of the present application first obtains a user group, and the user group includes multiple users having social relationships, and the plurality of users include the target.
  • Target users target users can be missing or inaccurate users for credit ratings. Since users in the user group have social relationships, the real credit scores of each user are relatively close.
  • the credit rating score of the user after the last iteration of the user having the social relationship determines the current credit score value of the user, and iteratively updates until the current credit score of each user in the user group satisfies the preset convergence result. , determine the target user's credit score value.
  • the solution of the present application relies on the credit score value of other users in the social circle of the target user to adjust or determine the credit score value of the target user, thereby improving the accuracy of the user's credit score, and solving the existing personal credit score calculation scheme. When the user's enough information is not obtained, the problem of his personal credit score cannot be accurately calculated.
  • FIG. 1 is a flowchart of a method for determining a credit score according to an embodiment of the present application
  • FIG. 2 is a schematic diagram of a social relationship diagram disclosed in an embodiment of the present application.
  • FIG. 3 is a flowchart of another method for determining a credit score according to an embodiment of the present application
  • FIG. 4 is a flowchart of still another method for determining a credit score according to an embodiment of the present application
  • FIG. 5 is a flowchart of still another method for determining a credit score according to an embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of a credit score determining apparatus according to an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of a rating update unit according to an embodiment of the present application.
  • FIG. 8 is a schematic structural diagram of a current credit rating value determining unit according to an embodiment of the present application.
  • FIG. 9 is a schematic structural diagram of a convergence determining unit according to an embodiment of the present disclosure.
  • FIG. 10 is a schematic structural diagram of a user group obtaining unit according to an embodiment of the present disclosure.
  • FIG. 11 is a schematic structural diagram of a server hardware according to an embodiment of the present disclosure.
  • FIG. 12 is a schematic structural diagram of a terminal according to an embodiment of the present disclosure.
  • FIG. 1 is a flowchart of a method for determining a credit score according to an embodiment of the present application.
  • the method includes steps S100 to S120.
  • Step S100 Acquire a user group, where the user group includes a plurality of users having a social relationship, and the plurality of users include the target user.
  • the target user may be unable to calculate the credit score value according to the existing credit score calculation model, or the calculated credit score value is inaccurate.
  • this embodiment may introduce the concept of intimacy between users, and use the intimacy values between users to characterize the distance between social relationships among users.
  • the determination of the intimacy value can be determined based on the amount of social communication between the two users, and can also be manually set.
  • the intimacy values are generally less than one.
  • Each user in the user group can calculate the initial credit score according to the existing credit score calculation model.
  • the initial credit score can be directly set.
  • the value is 0, or the initial credit score value of the user is determined according to the initial credit score value of each user who has a social relationship with the user, for example, the average of the initial credit score values of each user who has social relationships with the user.
  • the value is set to the user's initial credit score value.
  • Step S110 For each user in the user group, determine the current credit score value of the user according to the updated credit score value of the last iteration of the user having a social relationship with the user, and iteratively update until the user group The current credit score value of each user in the middle meets the preset convergence result.
  • Step S120 Determine a current credit score value of the target user as a credit score value of the target user.
  • the user's credit score value is closer to the real value.
  • the group can be identified.
  • the current credit score value of each user has reached the standard, and the current credit score value of the target user can be determined as the final credit score value.
  • the current credit scores of the users satisfy the preset convergence result, the current credit scores of the users in the group have reached the standard, and the current users of the users other than the target users in the user group may also be The credit score value is determined as the adjusted credit score value of the user.
  • the method for determining the credit score provided by the embodiment of the present application firstly obtains a user group, where the user group includes multiple users having social relationships, and the plurality of users include the target user, and the target user may be missing or inaccurate for the credit rating.
  • the user has a social relationship with each user in the user group, so the real credit scores of the users are relatively close.
  • the application for each user in the user group is based on the last iteration of the user who has a social relationship with the user.
  • the score value determines the current credit score value of the user, and iteratively updates until the current credit score value of each user in the user group satisfies the preset convergence result, and determines the credit score value of the target user.
  • the solution of the present application relies on the credit score value of other users in the social circle of the target user to adjust or determine the final credit score value of the target user, thereby improving the accuracy of the user's credit score.
  • the user's credit score value is affected by the credit score value of the user who has a social relationship with the user, and the user's credit score value may also affect the social relationship with the user.
  • User's credit rating value It can be understood that the farther the social relationship is, the smaller the intimacy value is, the smaller the impact on the other party's credit rating value.
  • a relationship threshold may be set to obtain only the user whose intimacy value with the target user is greater than the relationship threshold.
  • the updated credit scores of each user in the user group can be output as the latest credit score value.
  • the credit score values of multiple users are updated, so that the overall credit score value is updated more efficiently.
  • the social relationship diagram may also be established by using the social relationship between the users in the user group.
  • a social relationship diagram consists of a line segment between a node and a node.
  • the node represents the user.
  • the line segment between the nodes represents the direct social relationship between the users represented by the two nodes, and the online segment is characterized by the intimacy between the users represented by the two nodes. The value of the degree.
  • FIG. 2 is a schematic diagram of a social relationship diagram disclosed in an embodiment of the present application.
  • the social relationship diagram shown in Figure 2 contains a total of four users, namely users A, B, C, and D.
  • the relationship is a direct social relationship and an indirect social relationship, and the intimacy values of two users with indirect social relationships can be set to zero.
  • the users who have direct social relationship with A are B and C; the users who have direct social relationship with B are A and D; the users who have direct social relationship with C are A; and the users who have direct social relationship with D are B.
  • the social relationship between the remaining users is an indirect social relationship.
  • the intimacy value between users A and B is ⁇ ab
  • the intimacy value between users A and C is ⁇ ac
  • the intimacy value between users B and D is ⁇ bd .
  • the social relationship between each user in the user group is more vividly represented in the form of a legend.
  • the update process of the credit score value may be performed on each user in the social relationship map.
  • FIG. 3 is a flowchart of another method for determining a credit score according to an embodiment of the present application.
  • the method includes steps S300 to S330.
  • Step S300 Acquire a user group, where the user group includes a plurality of users having a social relationship, and the plurality of users include the target user.
  • the target user may be unable to calculate the credit score value according to the existing credit score calculation model, or the calculated credit score value is inaccurate.
  • Step S310 Perform a credit score update process on each user in the user group.
  • the credit score update process includes: determining a current credit score value of the user according to the updated credit score value of the last iteration of the user having a social relationship with the user.
  • the credit score values of each user in the user group are updated in turn, and the credit score value of the user who has a social relationship with the user is updated in the update. After updating the credit scores of each user in the user group, the user's credit score value is closer to the true credit score.
  • Step S320 Determine whether the current credit score value of each user in the user group satisfies the preset convergence result; if not, return to step S310, and if yes, execute step S330.
  • Step S330 Determine the current credit score value of the target user as the credit score value of the target user.
  • the user's credit score value is closer to the real value, and it is determined that the current credit scores of the users satisfy the preset convergence result. At this time, it can be determined that the current credit score value of each user in the group has reached the standard, and the current credit score value of the target user can be determined as the final credit score value.
  • the current credit score value of the remaining users of the user group except the target user may also be determined as the adjusted credit score value of the corresponding user.
  • This embodiment describes a specific implementation manner of iteratively updating the credit scores of users in the user group. By iteratively updating the credit scores of users in the user group, the credit scores of the users are truly true. The value is close.
  • This embodiment provides a user credit rating value update equation, and updates the credit score values of each user according to the following equation:
  • N is the total number of users in the user group.
  • ⁇ ij is the intimacy value between the i-th user and the j-th user, and the intimacy value represents the distance of the social relationship between the two users.
  • the credit score for the jth user after the t-1th update The initial credit score value for the i-th user.
  • the initial credit score value it can be calculated according to the existing calculation model.
  • the existing calculation model cannot calculate the initial credit score value of the user, the initial credit score value of the user may be set to 0, or the average value of the initial credit score value of the user who has a social relationship with the user. .
  • the intimacy value of the user i and the user j may be set to ⁇ ij
  • the intimacy value of the user j and the user i is ⁇ ji
  • ⁇ ij may be equal to ⁇ ji
  • ⁇ Ij can also be equal to ⁇ ji
  • the specific setting rules are determined according to actual needs.
  • PCS (t) ⁇ + Q * PCS (t-1)
  • PCS (n) can converge as long as Q n+1 is guaranteed to converge.
  • the intimacy of each user and its neighbor users is generally less than 1, and the neighbor users of the user are users who have social relationships with the user.
  • the user can be divided into a direct neighbor user and an indirect neighbor user
  • the direct neighbor user is a user having a direct social relationship with the user
  • the indirect neighbor user is a user having an indirect social relationship with the user.
  • the intimacy value between the user and the immediate neighbor user is not 0, and the intimacy value between the user and the indirect neighbor user can be set to 0.
  • the credit scores of A, B, C, and D have converged to certain results.
  • a 4 , B 4 , C 4 , and D 4 are very close to A 3 , B 3 , and C respectively. 3 , D 3 , and iteratively no longer changes, A 4 , B 4 , C 4 , D 4 can be output as the final value of the credit scores of A, B, C, D.
  • a 4 , B 4 , C 4 , D 4 are different from the original A 0 , B 0 , C 0 , D 0 , which is the influence of the friend's credit score.
  • the credit scores of the users B, C, and D can be B 4 .
  • C 4 and D 4 are the credit score values adjusted by the users B, C, and D, respectively.
  • the above credit scoring equation is only an optional form, and those skilled in the art can perform deformation and modification on the basis of the equation.
  • the method includes steps S400 to S450.
  • Step S400 Initializing the user group includes only the target user, and determining the target user as the designated user.
  • Step S410 Obtain a buddy list in the social network of the specified user.
  • step S420 it is determined whether there is a new user in the obtained buddy list, and the new user is a user that does not exist in the user group; if yes, step S430 is performed, and if no, step S440 is performed.
  • Step S430 adding the new user to the user group, and determining the new user as the designated user, and returning to step S410.
  • Step S440 Determine, for each user in the user group, the current credit score value of the user according to the updated credit score value of the last iteration of the user having a social relationship with the user, and iteratively update until the user group The current credit score value of each user in the middle meets the preset convergence result.
  • Step S450 Determine the current credit score value of the target user as the credit score value of the target user.
  • a specific implementation manner of acquiring a user group having a social relationship with a target user is introduced.
  • the user's social network is used to obtain a user's buddy list, and the buddy list of each user in the buddy list is further obtained and executed cyclically. Iterate over the update until no new users are available.
  • the user's social network may be various social networks of the user's QQ, WeChat, Weibo, Email, Address Book, and the like.
  • the method includes steps S500 to S530.
  • Step S500 Acquire a user group, where the user group includes a plurality of users having a social relationship, and the plurality of users include the target user.
  • the target user may be unable to calculate the credit score value according to the existing credit score calculation model, or the calculated credit score value is inaccurate.
  • Step S510 Perform a credit score update process on each user in the user group.
  • the credit score update process includes: determining a current credit score value of the user according to the updated credit score value of the last iteration of the user having a social relationship with the user.
  • Step S520 Determine whether the difference between the current credit score value of each user in the user group and the previous credit score value is less than a threshold. If yes, go to step S530, and if no, go back to step S510.
  • Step S530 Determine a current credit score value of the target user in the user group as a credit score value of the target user.
  • This embodiment introduces a method for judging whether the credit score value satisfies the convergence result, and specifically determines whether the credit score value satisfies the convergence result by comparing the difference between the difference between the score of the credit score before and after the update and the threshold.
  • the convergence value of each user's credit score value can be calculated in advance, and then each can be After the update, the updated credit score value and the convergence value are compared, and according to the comparison result, it is determined whether the updated credit score value satisfies the convergence result.
  • the credit score determining apparatus provided in the embodiment of the present application is described below, and the credit score determining apparatus described below and the credit score determining method described above can refer to each other.
  • FIG. 6 is a schematic structural diagram of a credit score determining apparatus according to an embodiment of the present application.
  • the device includes:
  • a user group obtaining unit 61 configured to acquire a user group, where the user group includes a plurality of users having a social relationship, and the plurality of users include the target user;
  • the score update unit 62 is configured to determine, for each user in the user group, the current credit score value of the user according to the last iteration updated credit score value of the user having a social relationship with the user, and iteratively update until The current credit score value of each user in the user group satisfies a preset convergence result;
  • the score value determining unit 63 is configured to determine the current credit score value of the target user as the credit score value of the target user.
  • the credit score determining apparatus first acquires a user group, where the user group includes multiple users having social relationships, and the plurality of users include the target user, and the target user may be missing or inaccurate for the credit rating.
  • the user has a social relationship with each user in the user group, so the real credit scores of the users are relatively close.
  • the application for each user in the user group is based on the last iteration of the user who has a social relationship with the user.
  • the score value determines the current credit score value of the user, and iteratively updates until the current credit score value of each user in the user group satisfies the preset convergence result, and determines the credit score value of the target user.
  • the solution of the present application relies on the credit score value of other users in the social circle of the target user to adjust or determine the final credit score value of the target user, thereby improving the accuracy of the user's credit score.
  • the embodiment of the present application discloses an optional structure of the above-mentioned score update unit 62.
  • the score update unit 62 may include:
  • the current credit score value determining unit 621 is configured to perform a credit score update process on each user in the user group, where the credit score update process includes: updating according to a last iteration of a user having a social relationship with the user The credit score value is used to determine the current credit score value of the user;
  • the convergence determining unit 622 is configured to determine whether the current credit score value of each user in the user group satisfies the preset convergence result; if not, return to execute the current credit score value determining unit 621, and if yes, end.
  • the embodiment of the present application discloses an optional structure of the current credit score value determining unit 621.
  • the current credit score value determining unit 621 may include:
  • the first current credit score value determining sub-element 6211 is configured to determine a current credit score value of the user according to the following formula:
  • N is the total number of users in the user group.
  • ⁇ ij is the intimacy value between the i-th user and the j-th user, and the intimacy value represents the distance of the social relationship between the two users.
  • the embodiment of the present application discloses an optional structure of the convergence determining unit 622.
  • the convergence determining unit 622 may include:
  • the first convergence judging sub-unit 6221 is configured to determine whether the difference between the current credit score value of each user in the user group and the credit score value after the last iteration update is less than a threshold, and if yes, determine the user group. The current credit scores of each user in the user meet the preset convergence result. If not, it is determined that the updated credit scores of the users in the user group do not all meet the preset convergence result.
  • the embodiment of the present application discloses an optional structure of the foregoing user group obtaining unit 61.
  • the user group obtaining unit 61 may include:
  • a first user group obtaining subunit 611 configured to initialize the user group to include only the target user, and determine the target user as the designated user;
  • a second user group obtaining sub-unit 612 configured to acquire a good social network in the specified user List of friends
  • a third user group obtaining sub-unit 613 configured to determine whether there is a new user in the obtained buddy list, where the new user is a user that does not exist in the user group, and if yes, executing a fourth user group obtaining sub-unit 614, if No, it ends;
  • the fourth user group acquisition sub-unit 614 is configured to add the new user to the user group, and determine the new user as a designated user, and then return to execute the second user group acquisition sub-unit 612.
  • the embodiment of the present application further provides a server, where the server includes the credit score determining device described above.
  • the server includes the credit score determining device described above.
  • the credit score determining device For the description of the credit score determining device, reference may be made to the corresponding part description above, and details are not described herein again.
  • FIG. 11 is a schematic structural diagram of a hardware of a server according to an embodiment of the present application.
  • the server may include:
  • Processor 1 communication interface 2, memory 3, communication bus 4, and display screen 5;
  • the processor 1, the communication interface 2, the memory 3, and the display screen 5 complete communication with each other through the communication bus 4;
  • the communication interface 2 can be an interface of the communication module, such as an interface of the GSM module;
  • a processor 1 for executing a program
  • a memory 3 for storing a program
  • the program can include program code, the program code including operational instructions of the processor.
  • the processor 1 may be a central processing unit CPU, or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.
  • CPU central processing unit
  • ASIC Application Specific Integrated Circuit
  • the memory 3 may include a high speed RAM memory and may also include a non-volatile memory such as at least one disk memory.
  • the program can be specifically used to:
  • the user group includes a plurality of users having social relationships, and the plurality of users include the target users;
  • the current credit score value of the target user is determined as the credit score value of the target user.
  • FIG. 12 is a block diagram of a credit score determining terminal 1100 according to an embodiment of the present invention.
  • the terminal 1100 may include:
  • RF (Radio Frequency) circuit 110 memory 120 including one or more computer readable storage media, input unit 130, display unit 140, sensor 150, audio circuit 160, WiFi (Wireless Fidelity) module 170.
  • a processor 180 having one or more processing cores, and a power supply 190 and the like. It will be understood by those skilled in the art that the terminal structure shown in FIG. 12 does not constitute a limitation to the terminal, and may include more or less components than those illustrated, or a combination of certain components, or different component arrangements. among them:
  • the RF circuit 110 can be used for transmitting and receiving information or during a call, and receiving and transmitting signals. Specifically, after receiving downlink information of the base station, the downlink information is processed by one or more processors 180. In addition, the data related to the uplink is sent to the base station. .
  • the RF circuit 110 includes, but is not limited to, an antenna, at least one amplifier, a tuner, one or more oscillators, a Subscriber Identity Module (SIM) card, a transceiver, a coupler, an LNA (Low Noise Amplifier). , duplexer, etc.
  • RF circuitry 110 can also communicate with the network and other devices via wireless communication.
  • the wireless communication may use any communication standard or protocol, including but not limited to GSM (Global System of Mobile communication), GPRS (General Packet Radio Service), CDMA (Code Division Multiple Access). , Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), LTE (Long Term Evolution), e-mail, SMS (Short Messaging Service), and the like.
  • GSM Global System of Mobile communication
  • GPRS General Packet Radio Service
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • LTE Long Term Evolution
  • e-mail Short Messaging Service
  • the memory 120 can be used to store software programs and modules, and the processor 180 executes various functional applications and data processing by running software programs and modules stored in the memory 120.
  • the memory 120 can mainly include a storage program area and a storage data area, wherein the storage program area can store an operating system, an application required for at least one function (such as a sound playing function, an image playing function).
  • the storage data area can store data (such as audio data, phone book, etc.) created according to the use of the terminal 1100.
  • memory 120 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, memory 120 may also include a memory controller to provide access to memory 120 by processor 180 and input unit 130.
  • the input unit 130 can be configured to receive input numeric or character information and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.
  • input unit 130 can include touch-sensitive surface 131 as well as other input devices 132.
  • Touch-sensitive surface 131 also referred to as a touch display or trackpad, can collect touch operations on or near the user (such as a user using a finger, stylus, etc., on any suitable object or accessory on touch-sensitive surface 131 or The operation in the vicinity of the touch-sensitive surface 131) is driven in accordance with a preset program to drive the device accordingly.
  • the touch-sensitive surface 131 can include two portions of a touch detection device and a touch controller.
  • the touch detection device detects the touch orientation of the user, and detects a signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts the touch information into contact coordinates, and sends the touch information.
  • the processor 180 is provided and can receive commands from the processor 180 and execute them.
  • the touch-sensitive surface 131 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves.
  • the input unit 130 can also include other input devices 132.
  • other input devices 132 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, joysticks, and the like.
  • the display unit 140 can be used to display information entered by the user or information provided to the user and various graphical user interfaces of the terminal 1100, which can be composed of graphics, text, icons, video, and any combination thereof.
  • the display unit 140 may include a display panel 141.
  • the display panel 141 may be configured in the form of an LCD (Liquid Crystal Display), an OLED (Organic Light-Emitting Diode), or the like.
  • the touch-sensitive surface 131 may cover the display panel 141, and when the touch-sensitive surface 131 detects a touch operation thereon or nearby, it is transmitted to the processor 180 to determine the type of the touch event, and then the processor 180 according to the touch event The type provides a corresponding visual output on display panel 141.
  • touch-sensitive surface 131 and display panel 141 are implemented as two separate components to implement input and input functions, in some embodiments, touch-sensitive surface 131 can be integrated with display panel 141 for input. And output function.
  • Terminal 1100 can also include at least one type of sensor 150, such as a light sensor, motion sensor, and other sensors.
  • the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 141 according to the brightness of the ambient light, and the proximity sensor may close the display panel 141 when the terminal 1100 moves to the ear. / or backlight.
  • the gravity acceleration sensor can detect the magnitude of acceleration in all directions (usually three axes). When it is stationary, it can detect the magnitude and direction of gravity.
  • the gesture of the mobile phone such as horizontal and vertical screen switching, related Game, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for the terminal 1,100 can also be configured with gyroscopes, barometers, hygrometers, thermometers, infrared sensors and other sensors, here Let me repeat.
  • the audio circuit 160, the speaker 161, and the microphone 162 can provide an audio interface between the user and the terminal 1100.
  • the audio circuit 160 can transmit the converted electrical data of the received audio data to the speaker 161 for conversion to the sound signal output by the speaker 161; on the other hand, the microphone 162 converts the collected sound signal into an electrical signal by the audio circuit 160. After receiving, it is converted into audio data, and then processed by the audio data output processor 180, transmitted to the terminal, for example, via the RF circuit 110, or outputted to the memory 120 for further processing.
  • the audio circuit 160 may also include an earbud jack to provide communication of the peripheral earphones with the terminal 1100.
  • WiFi is a short-range wireless transmission technology
  • the terminal 1100 can help users to send and receive emails, browse web pages, and access streaming media through the WiFi module 170, which provides wireless broadband Internet access for users.
  • FIG. 12 shows the WiFi module 170, it can be understood that it does not belong to the essential configuration of the terminal 1100, and may be omitted as needed within the scope of not changing the essence of the invention.
  • the processor 180 is a control center of the terminal 1100 that connects various portions of the entire handset with various interfaces and lines, by running or executing software programs and/or modules stored in the memory 120, and recalling data stored in the memory 120, The various functions and processing data of the terminal 1100 are performed to perform overall monitoring of the mobile phone.
  • the processor 180 may include one or more processing cores; preferably, the processor 180 may integrate an application processor and a modem processor, where the application processor mainly processes an operating system, a user interface, an application, and the like.
  • the modem processor primarily handles wireless communications. It can be understood that the above modem processor may not be integrated into the processor 180.
  • the terminal 1100 also includes a power supply 190 (such as a battery) for powering various components.
  • the power supply can be logically coupled to the processor 180 through a power management system to manage functions such as charging, discharging, and power management through the power management system.
  • Power supply 190 may also include any one or more of a DC or AC power source, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like.
  • the terminal 1100 may further include a camera, a Bluetooth module, and the like, and details are not described herein again.
  • the display unit of the terminal is a touch screen display
  • the terminal further includes a memory, and one or more programs, wherein one or more programs are stored in the memory and configured to be processed by one or more Execution.
  • the one or more programs include instructions for: acquiring a user group, the user group including a plurality of users having a social relationship, the plurality of users including the target user; and for each user in the user group, according to The credit rating score of the user after the last iteration of the user having the social relationship determines the current credit score value of the user, and iteratively updates until the current credit score of each user in the user group satisfies the preset convergence result. And determining the current credit score value of the target user as the credit score value of the target user.
  • the one or more programs further include instructions for performing other operations in the credit score determination method of FIG. 3, FIG. 4 or FIG. 5 described above.

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Abstract

一种征信评分确定方法及装置，所述方法包括：获取用户群，该用户群内包括具有社交关系的多个用户，多个用户中包含目标用户（S100），由于用户群内各用户具备社交关系，因此各个用户的真实征信评分相对比较接近，本方案对用户群内各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果（S110），确定目标用户的征信评分值（S120）。

Description

一种征信评分确定方法、装置及存储介质
本申请要求于2015年9月7日提交中国专利局、申请号为201510564542.6、发明名称为“一种征信评分确定方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及互联网技术领域，更具体地说，涉及一种征信评分确定方法、装置及存储介质。
背景技术
个人征信评分指的是征信评估机构利用征信评分模型对个人征信信息进行量化分析，以分值形式表达。
现有的个人征信评分计算技术主要是银行个人征信系统，其利用用户基本信息以及银行卡、信用卡的使用记录等，按照一定的计算模型计算个人征信评分。
发明内容
本申请提供了一种征信评分确定方法、装置及存储介质。
第一方面，本申请实施例提供一种征信评分确定方法，包括：
获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；
将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
第二方面，本申请实施例提供一种征信评分确定装置，包括：
用户群获取单元，用于获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
评分更新单元，用于对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；
评分值确定单元，用于将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
第三方面，本申请实施例提供一种征信评分确定装置，包括：
一个或多个处理器，配置为执行存储于存储介质上的程序指令，使所述征信评分确定装置执行：
获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；
将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
第四方面，本申请实施例提供一种非易失计算机可读存储介质，包括程序指令，所述程序指令当由处理器运行时，配置所述存储介质执行：
获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；
将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
从上述的技术方案可以看出，本申请实施例提供的征信评分确定方法，首先获取用户群，该用户群内包括具有社交关系的多个用户，多个用户中包含目 标用户，目标用户可以为征信评分缺失或不准确的用户，由于用户群内各用户具备社交关系，因此各个用户的真实征信评分相对比较接近，本申请对用户群内各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果，确定目标用户的征信评分值。本申请方案依靠目标用户的社交圈内其它用户的征信评分值来调整或确定目标用户的征信评分值，提高了用户的征信评分的准确度，可以解决现有个人征信评分计算方案在未获取用户的足够信息时，无法准确计算其个人征信评分的问题。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据提供的附图获得其他的附图。
图1为本申请实施例提供的一种征信评分确定方法流程图；
图2为本申请实施例公开的一个社交关系图的示意图；
图3为本申请实施例提供的另一种征信评分确定方法流程图；
图4为本申请实施例提供的又一种征信评分确定方法流程图；
图5为本申请实施例提供的又一种征信评分确定方法流程图；
图6为本申请实施例公开的一种征信评分确定装置结构示意图；
图7为本申请实施例公开的一种评分更新单元结构示意图；
图8为本申请实施例公开的一种当前征信评分值确定单元结构示意图；
图9为本申请实施例公开的一种收敛判断单元结构示意图；
图10为本申请实施例公开的一种用户群获取单元结构示意图；
图11为本申请实施例公开的一种服务器硬件结构示意图；以及
图12为本申请实施例公开的一种终端的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
参见图1，图1为本申请实施例提供的一种征信评分确定方法流程图。
如图1所示，该方法包括步骤S100至步骤S120。
步骤S100、获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户。
目标用户可以为按照现有征信评分计算模型无法计算出征信评分值，或者计算出的征信评分值不准确的用户。
为了表征用户群中各个用户之间的社交关系的远近，本实施例可以引入用户间的亲密度的概念，利用用户间的亲密度值来表征用户间社交关系的远近。亲密度值的确定可以根据两个用户间的社交通信量来确定，还可以人为进行设定等。亲密度值一般小于1。
用户群中的各个用户可以按照现有征信评分计算模型计算得到初始征信评分值，当然如果按照现有模型无法计算某个用户的征信评分值，则可以直接设定其初始征信评分值为0，或者按照与该用户具备社交关系的各个用户的初始征信评分值，确定该用户的初始征信评分值，例如，将与其具备社交关系的各个用户的初始征信评分值的平均值设定为该用户的初始征信评分值。
步骤S110、对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果。
步骤S120、将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
通过迭代更新用户群中各个用户的征信评分值，使得用户的征信评分值整体向真实值靠拢，当确定各个用户的当前征信评分值均满足预置收敛结果时，即可认定群中各个用户的当前征信评分值已经达标，此时可以将目标用户的当前征信评分值确定为最终的征信评分值。
当然，由于各个用户的当前征信评分值均满足预置收敛结果，群中各个用户的当前征信评分值已经达标，还可以将用户群中除目标用户外的其余用户中某个用户的当前征信评分值确定为该用户的调整后的征信评分值。
本申请实施例提供的征信评分确定方法，首先获取用户群，该用户群内包括具有社交关系的多个用户，多个用户中包含目标用户，目标用户可以为征信评分缺失或不准确的用户，由于用户群内各用户具备社交关系，因此各个用户的真实征信评分相对比较接近，本申请对用户群内各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果，确定目标用户的征信评分值。本申请方案依靠目标用户的社交圈内其它用户的征信评分值来调整或确定目标用户的最终的征信评分值，提高了用户的征信评分的准确度。
可选的，通过上述方案可以得知，用户的征信评分值受到与该用户具备社交关系的用户的征信评分值的影响，反过来用户的征信评分值也会影响与其具备社交关系的用户的征信评分值。可以理解的是，两个具备社交关系的用户，若其社交关系越远，也即亲密度值越小，则对对方的征信评分值的影响越小。
因此，为了减少计算复杂度，在获取与目标用户具备社交关系的用户时，可以设定一个关系阈值，仅获取与目标用户的亲密度值大于关系阈值的用户。
当然，如果不考虑计算复杂度的问题，可以将与目标用户具备社交关系的所有用户均添加到用户群中。这样，按照上述方案执行完毕后，用户群中各个用户更新后的征信评分值均可以作为各自最新的征信评分值进行输出。同时对多个用户的征信评分值进行更新，使得整体征信评分值更新效率更高。
进一步地，在获取了用户群之后，还可以利用所述用户群中各个用户间的社交关系建立社交关系图。社交关系图由节点和节点间的线段组成，其中节点代表用户，节点间的线段代表两个节点所代表的用户具备直接社交关系，并且在线段上赋有表征两个节点所代表的用户间的亲密度的值。
参见图2，图2为本申请实施例公开的一个社交关系图的示意图。图2示意的社交关系图中共包含4个用户，分别为用户A、B、C、D。我们将社 交关系为分直接社交关系和间接社交关系，具备间接社交关系的两个用户的亲密度值可以设置为0。
其中，与A具备直接社交关系的用户为B和C；与B具备直接社交关系的用户为A和D；与C具备直接社交关系的用户为A；与D具备直接社交关系的用户为B。剩余的用户间的社交关系为间接社交关系。
用户A与B间的亲密度值为αab，用户A与C间的亲密度值为αac，用户B与D间的亲密度值为αbd。
通过建立目标用户的社交关系图，以图例的形式更加形象的表明了用户群中各个用户之间的社交关系。在建立社交关系图之后，后续可以对社交关系图中的各个用户执行征信评分值的更新过程。
参见图3，图3为本申请实施例公开的另一种征信评分确定方法流程图。
如图3所示，该方法包括步骤S300至步骤S330。
步骤S300、获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户。
目标用户可以为按照现有征信评分计算模型无法计算出征信评分值，或者计算出的征信评分值不准确的用户。
步骤S310、对所述用户群中各个用户执行征信评分更新过程。
其中，所述征信评分更新过程包括：根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值。
本步骤中，依次对用户群中各个用户的征信评分值进行更新，更新时参考与用户具备社交关系的用户的征信评分值。在对用户群中各个用户的征信评分值均更新一遍后，用户的征信评分值整体向真实征信评分值靠拢。
步骤S320、判断所述用户群中各个用户的当前征信评分值是否均满足预置收敛结果；若否，返回执行步骤S310，若是，执行步骤S330。
步骤S330、将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
通过迭代更新用户群中各个用户的征信评分值，使得用户的征信评分值整体向真实值靠拢，当确定各个用户的当前征信评分值均满足预置收敛结果 时，即可认定群中各个用户的当前征信评分值已经达标，此时可以将目标用户的当前征信评分值确定为最终的征信评分值。
当然，还可以将用户群中除目标用户外的其余用户的当前征信评分值确定为对应用户的调整后的征信评分值。
本实施例介绍了一种对用户群内各个用户的征信评分值进行迭代更新的具体实施方式，通过迭代更新用户群中各个用户的征信评分值，使得用户的征信评分值整体向真实值靠拢。
在本申请的又一个实施例中，详细介绍上述利用与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值的过程。
本实施例提供了一种用户征信评分值更新方程，按照如下方程对各个用户的征信评分值进行更新：
Figure PCTCN2016097791-appb-000001
其中，N为用户群中用户总个数，
Figure PCTCN2016097791-appb-000002
为第i个用户在第t次更新后的征信评分值，αij为第i个用户与第j个用户间的亲密度值，亲密度值表征了两个用户间社交关系的远近，
Figure PCTCN2016097791-appb-000003
为第j个用户在第t-1次更新后的征信评分值，
Figure PCTCN2016097791-appb-000004
为第i个用户的初始征信评分值。
对于用户的初始征信评分值，可以按照现有的计算模型进行计算。当然，如果现有计算模型无法计算出用户的初始征信评分值，则可以设定用户的初始征信评分值为0，或者为与用户具备社交关系的用户的初始征信评分值的平均值。
可选的，在设定亲密度值时，可以设定用户i与用户j的亲密度值为αij，用户j与用户i的亲密度值为αji，αij可以等于αji，当然αij也可以不等于αji，具体设定规则根据实际需要而定。
接下来研究征信评分值的收敛情况。
将上述征信评分值更新方程按照矩阵形式表示：
Figure PCTCN2016097791-appb-000005
其中，定义：
Figure PCTCN2016097791-appb-000006
则征信评分值更新方程表示为：
PCS(t)＝β+Q*PCS(t-1)
则有如下推导：
第一次更新：PCS(1)＝β+Q*PCS(0)＝β+Q*β
第二次更新：PCS(2)＝β+Q*PCS(1)＝β+Q(β+Q*β)＝(I+Q+Q2)β
第三次更新：PCS(3)＝(I+Q+Q2+Q3)β
……
第n次更新：
Figure PCTCN2016097791-appb-000007
因此，只要保证Qn+1收敛，PCS(n)就能够收敛。
在实际应用中，一般令每个用户与其邻居用户的亲密度和小于1，用户的邻居用户为与用户具备社交关系的用户。
需要说明的是，上述公式中我们设定用户与自身之间的亲密度值为0。至于用户的邻居用户，可以分为直接邻居用户和间接邻居用户，直接邻居用户为与用户具备直接社交关系的用户；间接邻居用户为与用户具备间接社交关系的用户。用户与直接邻居用户间的亲密度值不为0，用户与间接邻居用户间的亲密度值可以设置为0。
接下来通过一个具体实例来介绍征信评分更新过程。
仍参见图2所示，假设A、B、C、D的初始征信评分为：
βa＝1＝A0，βb＝2＝B0，βc＝1＝C0，βd＝2＝D0
αab＝αac＝αba＝αbd＝αca＝αdb＝0.1
第一次迭代结果为：
A1＝βa+αabB0+αacC0＝1.3       B1＝βb+αbaA0+αbdD0＝2.3
C1＝βc+αcaA0＝1.1              D1＝βd+αdbB0＝2.2
第二次迭代结果为:
A2＝βa+αabB1+αacC1＝1.34      B2＝βb+αbaA1+αbdD1＝2.35
C2＝βc+αcaA1＝1.13            D2＝βd+αdbB1＝2.23
第三次迭代结果为:
A3＝βa+αabB2+αacC2＝1.348     B3＝βb+αbaA2+αbdD2＝2.357
C3＝βc+αcaA2＝1.134            D3＝βd+αdbB2＝2.235
第四次迭代结果为:
A4＝βa+αabB3+αacC3＝1.3491    B4＝βb+αbaA3+αbdD3＝2.3583
C4＝βc+αcaA3＝1.1348           D4＝βd+αdbB3＝2.2357
在迭代到第4次时，A、B、C、D的征信评分值已经收敛到一定结果，例如，A4，B4，C4，D4已经分别很接近A3，B3，C3，D3了，再迭代下去几乎就不再改变了，A4，B4，C4，D4可以作为A、B、C、D的征信评分值的最终值进行输出。A4，B4，C4，D4与最初的A0，B0，C0，D0比起来是有变化的，这就是好友的征信评分值产生的影响。
如果A是目标用户，由于各个用户(如A、B、C、D)的当前征信评分值均满足预置收敛结果,可以将此时用户B、C、D的征信评分值B4，C4，D4分别作为用户B、C、D调整后的征信评分值。当然上述征信评分方程仅仅是一种可选形式，本领域技术人员可以在此方程的基础上进行变形、改动。
在本申请的又一个实施例中，介绍了又一种征信评分值确定方法，参见图4。
如图4所示，该方法包括步骤S400至步骤S450。
步骤S400、初始化用户群仅包含目标用户，将所述目标用户确定为指定用户。
步骤S410、获取所述指定用户的社交网络中的好友列表。
步骤S420、判断获取的好友列表中是否存在新用户，所述新用户为所述用户群中不存在的用户；若是，则执行步骤S430，若否，执行步骤S440。
步骤S430、将所述新用户添加到所述用户群中，并将所述新用户确定为指定用户，返回执行步骤S410。
步骤S440、对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果。
步骤S450、将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
本实施例中介绍了一种获取与目标用户具备社交关系的用户群的具体实施方式，利用用户的社交网络来获取用户的好友列表，并进一步获取好友列表中各个用户的好友列表，循环执行，迭代更新直至获取不到新的用户为止。
这里，用户的社交网络可以是用户的QQ、微信、微博、Email、通讯录等等各种社交网络。
在本申请的又一个实施例中，介绍了又一种征信评分值确定方法，参见图5。
如图5所示，该方法包括步骤S500至步骤S530。
步骤S500、获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户。
目标用户可以为按照现有征信评分计算模型无法计算出征信评分值，或者计算出的征信评分值不准确的用户。
步骤S510、对所述用户群中各个用户执行征信评分更新过程。
其中，所述征信评分更新过程包括：根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值。
步骤S520、判断所述用户群中各用户的当前征信评分值与上一征信评分值的差值是否均小于阈值，若是，执行步骤S530，若否，返回执行步骤S510。
步骤S530、将所述用户群中目标用户的当前征信评分值确定为所述目标用户的征信评分值。
本实施例介绍了一种判断征信评分值是否满足收敛结果的方式，具体地通过对比更新前后征信评分值的差值与阈值的大小关系来确定征信评分值是否满足收敛结果。
可以理解的是，通过上一实施例中介绍的征信评分值更新方程，在确定各个用户间的亲密度值之后，可以预先计算出各个用户的征信评分值的收敛值，进而可以在每次更新后对比更新后的征信评分值与收敛值，根据对比结果来确定本次更新后的征信评分值是否满足收敛结果。
下面对本申请实施例提供的征信评分确定装置进行描述，下文描述的征信评分确定装置与上文描述的征信评分确定方法可相互对应参照。
参见图6，图6为本申请实施例公开的一种征信评分确定装置结构示意图。
如图6所示，该装置包括：
用户群获取单元61，用于获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
评分更新单元62，用于对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；
评分值确定单元63，用于将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
本申请实施例提供的征信评分确定装置，首先获取用户群，该用户群内包括具有社交关系的多个用户，多个用户中包含目标用户，目标用户可以为征信评分缺失或不准确的用户，由于用户群内各用户具备社交关系，因此各个用户的真实征信评分相对比较接近，本申请对用户群内各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果，确定目标用户的征信评分值。本申请方案依靠目标用户的社交圈内其它用户的征信评分值来调整或确定目标用户的最终征信评分值，提高了用户的征信评分的准确度。
可选的，本申请实施例公开了上述评分更新单元62的一种可选结构，如图7所示，评分更新单元62可以包括：
当前征信评分值确定单元621，用于对所述用户群中各个用户执行征信评分更新过程，所述征信评分更新过程包括：根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值；
收敛判断单元622，用于判断所述用户群中各个用户的当前征信评分值是否均满足预置收敛结果；若否，返回执行所述当前征信评分值确定单元621，若是，则结束。
可选的，本申请实施例公开了上述当前征信评分值确定单元621的一种可选结构，如图8所示，当前征信评分值确定单元621可以包括：
第一当前征信评分值确定子单元6211，用于按照下述公式确定用户的当前征信评分值：
Figure PCTCN2016097791-appb-000008
其中，N为用户群中用户总个数，
Figure PCTCN2016097791-appb-000009
为第i个用户在第t次更新后的征信评分值，αij为第i个用户与第j个用户间的亲密度值，亲密度值表征了两个用户间社交关系的远近，
Figure PCTCN2016097791-appb-000010
为第j个用户在第t-1次更新后的征信评分值。
可选的，本申请实施例公开了上述收敛判断单元622的一种可选结构，如图9所示，收敛判断单元622可以包括：
第一收敛判断子单元6221，用于判断所述用户群中各用户的当前征信评分值与上一次迭代更新后的征信评分值的差值是否均小于阈值，若是，确定所述用户群中各个用户的当前征信评分值均满足预置收敛结果，若否，确定所述用户群中各个用户更新后的征信评分值并非均满足预置收敛结果。
可选的，本申请实施例公开了上述用户群获取单元61的一种可选结构，如图10所示，用户群获取单元61可以包括：
第一用户群获取子单元611，用于初始化用户群仅包含目标用户，将所述目标用户确定为指定用户；
第二用户群获取子单元612，用于获取所述指定用户的社交网络中的好 友列表；
第三用户群获取子单元613，用于判断获取的好友列表中是否存在新用户，所述新用户为所述用户群中不存在的用户，若是，执行第四用户群获取子单元614，若否，则结束；
第四用户群获取子单元614，用于将所述新用户添加到所述用户群中，并将所述新用户确定为指定用户，然后返回执行所述第二用户群获取子单元612。
本申请实施例还提供一种服务器，该服务器包括上述所述的征信评分确定装置。对于征信评分确定装置的描述可参照上文对应部分描述，此处不再赘述。
本实施例对服务器的硬件结构进行介绍，参见图11，图11为本申请实施例提供的服务器的硬件结构示意图。如图11所示，该服务器可以包括：
处理器1，通信接口2，存储器3，通信总线4，和显示屏5；
其中处理器1、通信接口2、存储器3和显示屏5通过通信总线4完成相互间的通信；
可选的，通信接口2可以为通信模块的接口，如GSM模块的接口；
处理器1，用于执行程序；
存储器3，用于存放程序；
程序可以包括程序代码，所述程序代码包括处理器的操作指令。
处理器1可能是一个中央处理器CPU，或者是特定集成电路ASIC(Application Specific Integrated Circuit)，或者是被配置成实施本申请实施例的一个或多个集成电路。
存储器3可能包含高速RAM存储器，也可能还包括非易失性存储器(non-volatile memory)，例如至少一个磁盘存储器。
其中，程序可具体用于：
获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；
将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
图12是本发明实施例提供的一种征信评分值确定终端1100的框图。参见图12，所述终端1100可以包括：
RF(Radio Frequency，射频)电路110、包括有一个或一个以上计算机可读存储介质的存储器120、输入单元130、显示单元140、传感器150、音频电路160、WiFi(Wireless Fidelity，无线保真)模块170、包括有一个或者一个以上处理核心的处理器180、以及电源190等部件。本领域技术人员可以理解，图12中示出的终端结构并不构成对终端的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。其中：
RF电路110可用于收发信息或通话过程中，信号的接收和发送，特别地，将基站的下行信息接收后，交由一个或者一个以上处理器180处理；另外，将涉及上行的数据发送给基站。通常，RF电路110包括但不限于天线、至少一个放大器、调谐器、一个或多个振荡器、用户身份模块(SIM)卡、收发信机、耦合器、LNA(Low Noise Amplifier，低噪声放大器)、双工器等。此外，RF电路110还可以通过无线通信与网络和其他设备通信。所述无线通信可以使用任一通信标准或协议，包括但不限于GSM(Global System of Mobile communication，全球移动通讯系统)、GPRS(General Packet Radio Service，通用分组无线服务)、CDMA(Code Division Multiple Access，码分多址)、WCDMA(Wideband Code Division Multiple Access,宽带码分多址)、LTE(Long Term Evolution,长期演进)、电子邮件、SMS(Short Messaging Service，短消息服务)等。
存储器120可用于存储软件程序以及模块，处理器180通过运行存储在存储器120的软件程序以及模块，从而执行各种功能应用以及数据处理。存储器120可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序(比如声音播放功能、图像播放功能 等)等；存储数据区可存储根据终端1100的使用所创建的数据(比如音频数据、电话本等)等。此外，存储器120可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。相应地，存储器120还可以包括存储器控制器，以提供处理器180和输入单元130对存储器120的访问。
输入单元130可用于接收输入的数字或字符信息，以及产生与用户设置以及功能控制有关的键盘、鼠标、操作杆、光学或者轨迹球信号输入。具体地，输入单元130可包括触敏表面131以及其他输入设备132。触敏表面131，也称为触摸显示屏或者触控板，可收集用户在其上或附近的触摸操作(比如用户使用手指、触笔等任何适合的物体或附件在触敏表面131上或在触敏表面131附近的操作)，并根据预先设定的程式驱动相应地连接装置。可选的，触敏表面131可包括触摸检测装置和触摸控制器两个部分。其中，触摸检测装置检测用户的触摸方位，并检测触摸操作带来的信号，将信号传送给触摸控制器；触摸控制器从触摸检测装置上接收触摸信息，并将它转换成触点坐标，再送给处理器180，并能接收处理器180发来的命令并加以执行。此外，可以采用电阻式、电容式、红外线以及表面声波等多种类型实现触敏表面131。除了触敏表面131，输入单元130还可以包括其他输入设备132。具体地，其他输入设备132可以包括但不限于物理键盘、功能键(比如音量控制按键、开关按键等)、轨迹球、鼠标、操作杆等中的一种或多种。
显示单元140可用于显示由用户输入的信息或提供给用户的信息以及终端1100的各种图形用户接口，这些图形用户接口可以由图形、文本、图标、视频和其任意组合来构成。显示单元140可包括显示面板141，可选的，可以采用LCD(Liquid Crystal Display，液晶显示器)、OLED(Organic Light-Emitting Diode,有机发光二极管)等形式来配置显示面板141。进一步的，触敏表面131可覆盖显示面板141，当触敏表面131检测到在其上或附近的触摸操作后，传送给处理器180以确定触摸事件的类型，随后处理器180根据触摸事件的类型在显示面板141上提供相应地视觉输出。虽然在图11中，触敏表面131与显示面板141是作为两个独立的部件来实现输入和输入功能，但是在某些实施例中，可以将触敏表面131与显示面板141集成而实现输入 和输出功能。
终端1100还可包括至少一种传感器150，比如光传感器、运动传感器以及其他传感器。具体地，光传感器可包括环境光传感器及接近传感器，其中，环境光传感器可根据环境光线的明暗来调节显示面板141的亮度，接近传感器可在终端1100移动到耳边时，关闭显示面板141和/或背光。作为运动传感器的一种，重力加速度传感器可检测各个方向上(一般为三轴)加速度的大小，静止时可检测出重力的大小及方向，可用于识别手机姿态的应用(比如横竖屏切换、相关游戏、磁力计姿态校准)、振动识别相关功能(比如计步器、敲击)等；至于终端1100还可配置的陀螺仪、气压计、湿度计、温度计、红外线传感器等其他传感器，在此不再赘述。
音频电路160、扬声器161，传声器162可提供用户与终端1100之间的音频接口。音频电路160可将接收到的音频数据转换后的电信号，传输到扬声器161，由扬声器161转换为声音信号输出；另一方面，传声器162将收集的声音信号转换为电信号，由音频电路160接收后转换为音频数据，再将音频数据输出处理器180处理后，经RF电路110以发送给比如另一终端，或者将音频数据输出至存储器120以便进一步处理。音频电路160还可能包括耳塞插孔，以提供外设耳机与终端1100的通信。
WiFi属于短距离无线传输技术，终端1100通过WiFi模块170可以帮助用户收发电子邮件、浏览网页和访问流式媒体等，它为用户提供了无线的宽带互联网访问。虽然图12示出了WiFi模块170，但是可以理解的是，其并不属于终端1100的必须构成，完全可以根据需要在不改变发明的本质的范围内而省略。
处理器180是终端1100的控制中心，利用各种接口和线路连接整个手机的各个部分，通过运行或执行存储在存储器120内的软件程序和/或模块，以及调用存储在存储器120内的数据，执行终端1100的各种功能和处理数据，从而对手机进行整体监控。可选的，处理器180可包括一个或多个处理核心；优选的，处理器180可集成应用处理器和调制解调处理器，其中，应用处理器主要处理操作系统、用户界面和应用程序等，调制解调处理器主要处理无线通信。可以理解的是，上述调制解调处理器也可以不集成到处理器180中。
终端1100还包括给各个部件供电的电源190(比如电池)，优选的，电源可以通过电源管理系统与处理器180逻辑相连，从而通过电源管理系统实现管理充电、放电、以及功耗管理等功能。电源190还可以包括一个或一个以上的直流或交流电源、再充电系统、电源故障检测电路、电源转换器或者逆变器、电源状态指示器等任意组件。
尽管未示出，终端1100还可以包括摄像头、蓝牙模块等，在此不再赘述。具体在本实施例中，终端的显示单元是触摸屏显示器，终端还包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行。所述一个或者一个以上程序包含用于执行以下操作的指令：获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
所述一个或者一个以上程序还包含用于执行上述图3，图4或图5中的征信评分确定方法中其他操作的指令。
最后，还需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
本说明书中各个实施例采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似部分互相参见即可。
对所公开的实施例的上述说明，使本领域专业技术人员能够实现或使用本 申请。对这些实施例的多种修改对本领域的专业技术人员来说将是显而易见的，本文中所定义的一般原理可以在不脱离本申请的精神或范围的情况下，在其它实施例中实现。因此，本申请将不会被限制于本文所示的这些实施例，而是要符合与本文所公开的原理和新颖特点相一致的最宽的范围。

Claims (12)

  1. 一种征信评分确定方法，其特征在于，包括：
    获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
    对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；以及
    将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
  2. 根据权利要求1所述的方法，其特征在于，所述对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果，包括：
    对所述用户群中各个用户执行征信评分更新过程，所述征信评分更新过程包括：根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值；
    判断所述用户群中各个用户的当前征信评分值是否均满足预置收敛结果；
    若否，返回执行所述对所述用户群中各个用户执行征信评分更新过程的步骤；
    若是，则结束。
  3. 根据权利要求2所述的方法，其特征在于，所述根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，包括：
    按照下述公式确定用户的当前征信评分值：
    Figure PCTCN2016097791-appb-100001
    其中，N为用户群中用户总个数，
    Figure PCTCN2016097791-appb-100002
    为第i个用户在第t次更新后的征信评分值，αij为第i个用户与第j个用户间的亲密度值，亲密度值表征了两个 用户间社交关系的远近，
    Figure PCTCN2016097791-appb-100003
    为第j个用户在第t-1次更新后的征信评分值，
    Figure PCTCN2016097791-appb-100004
    为第i个用户的初始征信评分值。
  4. 根据权利要求2所述的方法，其特征在于，所述判断所述用户群中各个用户的当前征信评分值是否均满足预置收敛结果，包括：
    判断所述用户群中各用户的当前征信评分值与上一次迭代更新后的征信评分值的差值是否均小于阈值，若是，确定所述用户群中各个用户的当前征信评分值均满足预置收敛结果，若否，确定所述用户群中各个用户更新后的征信评分值并非均满足预置收敛结果。
  5. 根据权利要求1所述的方法，其特征在于，所述获取用户群，包括：
    初始化用户群仅包含目标用户，将所述目标用户确定为指定用户；
    获取所述指定用户的社交网络中的好友列表；
    判断获取的好友列表中是否存在新用户，所述新用户为所述用户群中不存在的用户；
    若是，则将所述新用户添加到所述用户群中，并将所述新用户确定为指定用户，返回执行所述获取所述指定用户的社交网络中的好友列表的步骤；
    若否，则结束。
  6. 一种征信评分确定装置，其特征在于，包括：
    用户群获取单元，用于获取用户群，用户群包括具备社交关系的多个用户，多个用户中包含目标用户；
    评分更新单元，用于对于所述用户群中各个用户，根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值，迭代更新直至所述用户群中各个用户的当前征信评分值满足预置收敛结果；以及
    评分值确定单元，用于将所述目标用户的当前征信评分值确定为目标用户的征信评分值。
  7. 根据权利要求6所述的装置，其特征在于，所述评分更新单元包括：
    当前征信评分值确定单元，用于对所述用户群中各个用户执行征信评分更新过程，所述征信评分更新过程包括：根据与用户具有社交关系的用户的上一次迭代更新后的征信评分值，确定所述用户的当前征信评分值；
    收敛判断单元，用于判断所述用户群中各个用户的当前征信评分值是否均 满足预置收敛结果；若否，返回执行所述当前征信评分值确定单元，若是，则结束。
  8. 根据权利要求7所述的装置，其特征在于，所述当前征信评分值确定单元包括：
    第一当前征信评分值确定子单元，用于按照下述公式确定用户的当前征信评分值：
    Figure PCTCN2016097791-appb-100005
    其中，N为用户群中用户总个数，
    Figure PCTCN2016097791-appb-100006
    为第i个用户在第t次更新后的征信评分值，αij为第i个用户与第j个用户间的亲密度值，亲密度值表征了两个用户间社交关系的远近，
    Figure PCTCN2016097791-appb-100007
    为第j个用户在第t-1次更新后的征信评分值，
    Figure PCTCN2016097791-appb-100008
    为第i个用户的初始征信评分值。
  9. 根据权利要求7所述的装置，其特征在于，所述收敛判断单元包括：
    第一收敛判断子单元，用于判断所述用户群中各用户的当前征信评分值与上一次迭代更新后的征信评分值的差值是否均小于阈值，若是，确定所述用户群中各个用户的当前征信评分值均满足预置收敛结果，若否，确定所述用户群中各个用户更新后的征信评分值并非均满足预置收敛结果。
  10. 根据权利要求6所述的装置，其特征在于，所述用户群获取单元包括：
    第一用户群获取子单元，用于初始化用户群为空值，将所述目标用户确定为指定用户；
    第二用户群获取子单元，用于获取所述指定用户的社交网络中的好友列表；
    第三用户群获取子单元，用于判断获取的好友列表中是否存在新用户，所述新用户为所述用户群中不存在的用户，若是，执行第四用户群获取子单元，若否，则结束；
    第四用户群获取子单元，用于将所述新用户添加到所述用户群中，并将所述新用户确定为指定用户，然后返回执行所述第二用户群获取子单元。
  11. 一种征信评分确定装置，其特征在于，包括：
    一个或多个处理器，配置为执行存储于存储介质上的程序指令，使所述征信评分确定装置执行权利要求1-5中任意一项所述的征信评分确定方法。
  12. 一种非易失计算机可读存储介质，包括程序指令，所述程序指令当由处理器运行时，配置所述存储介质执行权利要求1-5中任意一项所述的征信评分确定方法。
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