CN112396508A - Social credit public inquiry system based on big data - Google Patents

Social credit public inquiry system based on big data Download PDF

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CN112396508A
CN112396508A CN202011262965.XA CN202011262965A CN112396508A CN 112396508 A CN112396508 A CN 112396508A CN 202011262965 A CN202011262965 A CN 202011262965A CN 112396508 A CN112396508 A CN 112396508A
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query result
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big data
enterprise
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CN112396508B (en
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欧泽超
王元聪
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Shanghai Jingdi Credit Management Co ltd
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    • 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
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    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2471—Distributed queries
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    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/3349—Reuse of stored results of previous queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques

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Abstract

The invention provides a social credit bulletin inquiry system based on big data, comprising: the device comprises an input module, a query module, a big data analysis module and a display module; the input module is used for inputting information to be inquired; the inquiry module is used for inquiring once from the credit information disclosing system according to the information to be inquired and outputting a corresponding inquiry result; the big data analysis module is used for extracting the label of the primary query result, analyzing the big data according to the obtained label information and outputting a corresponding secondary query result; the display module is used for displaying the primary query result and the secondary query result corresponding to the primary query result. The invention is helpful for the user to further know the credit condition of the target object and simultaneously improves the intelligent level of the query system.

Description

Social credit public inquiry system based on big data
Technical Field
The invention relates to the technical field of big data, in particular to a social credit bulletin query system based on big data.
Background
The credit investigation system is an important component of a social credit system, and the sound credit investigation system is not only beneficial to financial institutions to control credit risks, is convenient for financial supervision institutions to carry out risk early warning analysis, is beneficial to judicial departments and other government agencies to standardize financial orders, but also can protect the benefits of consumers.
The current credit investigation system is usually created by a single credit investigation institution (such as a bank, a government agency), in the credit investigation system of the credit investigation institution, the credit investigation institution can generate credit investigation data for the enterprise user based on the credit behavior of the enterprise user at the credit investigation institution, and the like, and store the credit investigation data in the credit investigation system of the credit investigation institution to realize the inquiry function of the enterprise user and the reference function of other services.
The existing credit investigation system inputs a specific investigation target (individual or enterprise), and then the system displays credit investigation information related to the target, but for individuals or enterprises without credit investigation records, any related information cannot be investigated, and the requirement of modern credit investigation information construction cannot be met.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a social credit bulletin query system based on big data.
The purpose of the invention is realized by adopting the following technical scheme:
a social credit public inquiry system based on big data is provided, which comprises: the device comprises an input module, a query module, a big data analysis module and a display module; wherein the content of the first and second substances,
the input module is used for inputting information to be inquired;
the inquiry module is used for inquiring once from the credit information disclosing system according to the information to be inquired and outputting a corresponding inquiry result;
the big data analysis module is used for extracting the label of the primary query result, analyzing the big data according to the obtained label information and outputting a corresponding secondary query result;
the display module is used for displaying the primary query result and the secondary query result corresponding to the primary query result.
In one embodiment, the result of a query includes tagged information of an individual or business, as well as basic information and social credit information corresponding to the individual or business.
In one embodiment, the big data analysis module comprises a personal analysis unit and an enterprise analysis unit;
the enterprise analysis unit is used for acquiring a corresponding enterprise tag according to the basic information of the enterprise when the primary query result is the enterprise, performing big data analysis according to the acquired tag information, and outputting a corresponding secondary query result;
the personal analysis unit is used for acquiring a corresponding label according to personal basic information of a primary query result when the primary query result is personal, performing big data analysis according to the acquired label information and outputting a corresponding secondary query result;
in one embodiment, the enterprise analysis unit further comprises: and acquiring the main personnel information of the enterprise according to the basic information of the enterprise, inputting the main personnel information into a personal analysis unit, analyzing the main personnel by the personal analysis unit, and outputting a corresponding secondary query result.
In one embodiment, the system further comprises a big database module;
the big database module is used for storing basic information of individuals and enterprises, social credit information and corresponding label information of the individuals and the enterprises.
The invention has the beneficial effects that: the invention is provided with the big data analysis module, further carries out big data analysis processing on the primary query result, extracts the corresponding secondary query result according to the big data analysis result, and particularly can provide credit investigation information of the secondary query result as reference under the condition that the credit investigation information of a target individual or enterprise in the primary query result is incomplete or has no record, thereby improving the intelligent level of the query system.
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The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a block diagram of the frame of the present invention;
FIG. 2 is a block diagram of a big data analysis module according to the present invention.
Reference numerals:
input module 1, query module 2, big data analysis module 3, display module 4, personal analysis unit 31, enterprise analysis unit 32
Detailed Description
The invention is further described in connection with the following application scenarios.
Referring to fig. 1, a big data based social credit public query system is shown, comprising: the device comprises an input module 1, an inquiry module 2, a big data analysis module 3 and a display module 4; wherein the content of the first and second substances,
the input module 1 is used for inputting information to be inquired;
the query module 2 is used for carrying out one-time query from the credit information publicity system according to the information to be queried and outputting a corresponding one-time query result;
the big data analysis module 3 is used for extracting labels of the primary query results, analyzing the big data according to the obtained label information and outputting corresponding secondary query results;
the display module 4 is used for displaying the primary query result and the secondary query result corresponding to the primary query result.
Wherein, the one-time query result comprises the marking information of the individual or the enterprise, and the basic information and the social credit information corresponding to the individual or the enterprise.
In the above embodiment, the query module is arranged in the query system to query the target information to be queried input by the user once, and basic information and social credit information of the query target object in the public credit information disclosure system are displayed for the user to directly know the social credit information of the target object; meanwhile, the big data analysis module 3 can also perform big data analysis according to the basic information of the target object to acquire credit information of other objects related to the target object, so that the user can perform transverse comparison or reference according to the big data analysis result, the user can further know the credit condition of the target object, and the intelligence level of the query system is improved.
The information to be queried input by the input module comprises an enterprise name, a personal name, keyword information and the like. The output query result may be a single query target, or may be a result list meeting the requirements, and the list includes the individuals or businesses meeting the requirements, the corresponding basic information and credit information, and the like.
In one embodiment, the basic information of the individual includes a personal name, location information including a place of residence or a place of residence, marital status, work unit, and the like;
the basic information of the enterprise comprises enterprise names, legal person information, registration places, investors, main personnel, general branch institutions, change records, litigation information, administrative penalty records, intellectual property rights, registered trademarks, media evaluation and the like;
the social credit information includes the credit-keeping behavior, the number of times of the credit-keeping behavior, the violation behavior, the number of times of the violation behavior, the social credit score, and the like.
The credit information publicizing system records the basic information of the individual or the enterprise and the corresponding social credit information, and by inputting the corresponding target object name, the basic information of the relevant individual or the enterprise and the social credit information can be searched from the search engine of the credit information publicizing system.
The credit information publicizing system comprises a government-built official national enterprise credit information publicizing system and a personal credit investigation system, and can also be an internal credit information investigation system built by enterprises or enterprise unions (such as banks, financial institutions, credit institutions and the like); the present invention may be an existing credit information inquiry system, or may be other credit information inquiry systems, and the present application is not limited in particular herein.
Aiming at the coverage rate or incomplete information possibly existing in the existing credit information inquiry system, the condition that the credit information of partial target individuals or target enterprises is incomplete or no credit information is recorded possibly exists, so that the credit condition of a target object cannot be known; therefore, the method and the device are built based on the existing credit information inquiry system, and on the basis of the existing credit information inquiry system, the inquiry result is further subjected to big data analysis processing, so that the target object, particularly the target object lacking credit information records, can be effectively further analyzed and processed, and a user can be helped to further evaluate the target object according to the big data analysis result to provide an effective information basis.
In one embodiment, referring to FIG. 2, big data analysis module 3 includes a personal analysis unit 31 and an enterprise analysis unit 32;
the enterprise analysis unit 32 is configured to, when the primary query result is an enterprise, obtain a corresponding enterprise tag according to the basic information of the enterprise, perform big data analysis according to the obtained tag information, and output a corresponding secondary query result;
the personal analysis unit 31 is configured to, when the primary query result is a person, obtain a corresponding tag according to the personal basic information of the primary query result, perform big data analysis according to the obtained tag information, and output a corresponding secondary query result.
When the query module 2 obtains the query results from the credit information formula system according to the information to be queried, which are individuals or enterprises, respectively, the big data analysis module 3 of the present application is provided with a special enterprise analysis unit 32 and a special individual analysis unit 31 to perform further big data analysis processing on the primary query results of different types, which is helpful for setting different big data analysis algorithms according to different types of individuals or enterprises, searching corresponding target data from a big database for analysis, and improving the accuracy of the big data analysis results.
In a reference embodiment, when the primary query result is an individual, the individual analysis unit 31 performs further big data analysis on the basic information and credit information of the individual obtained from the primary query result, first performs feature extraction on the basic information of the individual in the primary query result, identifies tag information (such as age, place of residence, marital status, work unit, etc.) corresponding to the target individual, screens out other personal information and corresponding credit information corresponding to the tag information from the big database as an analysis sample according to the acquired tag information, performs data screening or cluster analysis on the analysis sample, and acquires reference credit information (such as related warning information corresponding to the tag, predicted credit score, average credit score of the analysis sample, etc.) as an output secondary query result.
In one scenario, only relevant basic information exists in a query result of a target individual acquired in the query module, and no record about credit information exists; based on the above one-time query result, the personal analysis unit performs feature extraction according to the basic information of the target person, and obtains tag information of the target person, namely 'xx years old, YY village in residence, no marriage, no work unit and the like'; the personal analysis unit further screens out analysis samples corresponding to the label information from a big database according to the label information, and inputs credit information corresponding to the analysis samples into a cluster analysis model for analysis to obtain corresponding prediction credit scores; meanwhile, retrieval is carried out according to the obtained label information, after information such as YY village which is officially marked as 'honest demonstration village' by the government is retrieved, the information is used as label warning information and is output together with the predicted credit score to be used as a secondary query result for a user to comprehensively know and evaluate the information related to the target individual, the method is beneficial to the user to obtain related reference information from a large database of multi-party information to be used as a basis under the condition that the target individual does not have any credit information record, and the width of a reference obtaining channel of the credit information of the information target individual by the user is improved.
In one embodiment, enterprise analysis unit 32 further includes: and acquiring the main personnel information of the enterprise according to the basic information of the enterprise, inputting the main personnel information into the personal analysis unit 31, analyzing the main personnel by the personal analysis unit 31, and outputting a corresponding secondary query result.
In a reference embodiment, when the primary query result is an enterprise, the enterprise analysis unit 32 performs further big data analysis based on the basic information and credit information of the target enterprise of the primary query result, first performs feature extraction based on the enterprise basic information of the primary query result, identifies tag information (such as legal information, a registered place, investor information, main person information, change records, litigation information, administrative penalty records, intellectual property right amount, registered trademark amount, media evaluation, etc.) corresponding to the target enterprise, screens out other personal information and corresponding credit information corresponding to the tag information from the big database as an analysis sample based on the acquired tag information, inputs the basic information of the analysis sample as a training sample, outputs the credit information of the analysis sample as a training sample, trains the clustering model, acquiring a trained clustering model, inputting label information of the target enterprise into the trained clustering model as an input parameter, and displaying prediction credit information (credit score) output by the acquired clustering model in a secondary query result; meanwhile, label information with the largest influence on credit score prediction is marked and displayed in a secondary query result. Meanwhile, after the enterprise analysis unit 32 acquires the personal information related to the enterprise, the personal information is input to the personal analysis unit 31, the personal analysis unit 31 further analyzes the big data of the related person, and the acquired result is also displayed in the secondary query result. Through the enterprise analysis unit 32, deep big data mining analysis can be performed on the enterprise according to the basic information of the enterprise, and the target enterprise is transversely evaluated on the basis of the data stored in the big database, so that the user can serve as reference information, and the intelligent level of the query system is improved.
In one scenario, the enterprise analysis unit 32 obtains the corporate ZZ of the enterprise, inputs the corporate ZZ into a trained cluster model as an input parameter, and marks and displays the ZZ in a secondary query result when it is detected by the cluster model that the corporate ZZ is the largest factor (for example, ZZ is a person who loses credit and is open to the public) affecting credit score, so that a user can know that the corporate ZZ is a person who loses credit even though there is no credit record for a target enterprise, and the user can be used as a reference for evaluating the target enterprise.
Meanwhile, the enterprise analysis unit 32 inputs the information of the person ZZ into the personal analysis unit 31, and the personal analysis unit 31 performs big data analysis on the information of the person ZZ according to the basic information of the person ZZ to obtain an analysis result related to the person, and the analysis result is displayed in a secondary query result.
In one embodiment, the system further comprises a big database module;
the big database module is used for storing basic information of individuals and enterprises, social credit information and corresponding label information of the individuals and the enterprises.
The large database module can automatically acquire related information of individuals or enterprises from public data sources, perform data screening, feature extraction and other processing on the acquired information, automatically generate label information corresponding to the individuals or the enterprises, and bind the acquired label information with the individuals or the enterprises. Meanwhile, credit information corresponding to each person or enterprise is recorded in the large database. And the related data for displaying the secondary query result.
The inquiry system of the invention establishes a perfect big database as the basis of a big data analysis module on the basis of the existing credit information publicity system, screens and classifies and stores the massive basic information and credit information of individuals and enterprises, and provides guarantee for the accuracy of big data analysis of the inquiry system.
It should be noted that, functional units/modules in the embodiments of the present invention may be integrated into one processing unit/module, or each unit/module may exist alone physically, or two or more units/modules are integrated into one unit/module. The integrated units/modules may be implemented in the form of hardware, or may be implemented in the form of software functional units/modules.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, a processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be analyzed by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (5)

1. A social credit bulletin query system based on big data, comprising: the device comprises an input module, a query module, a big data analysis module and a display module;
the input module is used for inputting information to be inquired;
the inquiry module is used for inquiring once from the credit information disclosing system according to the information to be inquired and outputting a corresponding inquiry result;
the big data analysis module is used for extracting the label of the primary query result, analyzing the big data according to the obtained label information and outputting a corresponding secondary query result;
the display module is used for displaying the primary query result and the secondary query result corresponding to the primary query result.
2. The big-data-based social credit bulletin query system of claim 1, wherein the one-time query result comprises tag information of an individual or a business, and basic information and social credit information corresponding to the individual or the business.
3. The big-data-based social credit publicity query system of claim 2, wherein the big data analysis module comprises a personal analysis unit and an enterprise analysis unit;
the enterprise analysis unit is used for acquiring a corresponding enterprise tag according to the basic information of the enterprise when the primary query result is the enterprise, performing big data analysis according to the acquired tag information, and outputting a corresponding secondary query result;
and the personal analysis unit is used for acquiring a corresponding label according to the personal basic information of the primary query result when the primary query result is personal, performing big data analysis according to the acquired label information, and outputting a corresponding secondary query result.
4. The big-data based social credit publicity query system as claimed in claim 3, wherein said enterprise analysis unit further comprises: and acquiring the main personnel information of the enterprise according to the basic information of the enterprise, inputting the main personnel information into the personal analysis unit, analyzing the main personnel by the personal analysis unit, and outputting the corresponding secondary query result.
5. A big data based social credit communiation query system according to claim 4, further comprising a big database module;
the big database module is used for storing the basic information, the social credit information and the corresponding label information of the individuals and the enterprises.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106372215A (en) * 2016-09-06 2017-02-01 江苏通付盾科技有限公司 Credit inquiring system and method
CN106649453A (en) * 2016-09-22 2017-05-10 上海市数字证书认证中心有限公司 Enterprise credit query and display method and system
CN107392820A (en) * 2017-06-30 2017-11-24 苏州吉耐特信息科技有限公司 A kind of multiple enterprises information integrated query web station system
CN108648368A (en) * 2018-03-19 2018-10-12 南京市信息中心 A kind of common credit information shared system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106372215A (en) * 2016-09-06 2017-02-01 江苏通付盾科技有限公司 Credit inquiring system and method
CN106649453A (en) * 2016-09-22 2017-05-10 上海市数字证书认证中心有限公司 Enterprise credit query and display method and system
CN107392820A (en) * 2017-06-30 2017-11-24 苏州吉耐特信息科技有限公司 A kind of multiple enterprises information integrated query web station system
CN108648368A (en) * 2018-03-19 2018-10-12 南京市信息中心 A kind of common credit information shared system

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