CN112396508B - Social credit public query system based on big data - Google Patents
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Abstract
The invention provides a social credit public inquiry system based on big data, comprising: the system 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 queried; the query module is used for carrying out one-time query from the credit information display system according to the information to be queried and outputting a corresponding one-time query 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 improves the intelligent level of the query system.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a social credit public inquiry 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 beneficial to a financial institution to control credit risks, is convenient for a financial supervision institution to carry out risk early warning analysis, is beneficial to a judicial department and other government institutions to standardize financial order, and can also protect consumer interests.
Current credit systems are typically created by a single credit agency (e.g., bank, government agency), in which the credit agency can generate credit data for enterprise users based on their credit behaviors of the enterprise users in the credit agency, etc., and store the generated credit data in the credit agency's credit system to realize enterprise user's inquiry and reference functions as other services.
The existing credit inquiry system inputs a specific inquiry target (individual or enterprise), then the system displays credit information related to the target, but aiming at the individual or enterprise without credit records, any related information cannot be inquired, and the requirements of modern credit inquiry information construction cannot be met.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a social credit public inquiry system based on big data.
The aim 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 system comprises an input module, a query module, a big data analysis module and a display module; wherein,
The input module is used for inputting information to be queried;
The query module is used for carrying out one-time query from the credit information display system according to the information to be queried and outputting a corresponding one-time query 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, a query result includes tag information of an individual or business, and 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 corresponding enterprise labels according to basic information of the enterprise when the primary query result is the enterprise, analyzing big data according to the acquired label information and outputting a corresponding secondary query result;
The personal analysis unit is used for acquiring corresponding labels according to personal basic information of the primary query result when the primary query result is personal, analyzing big data according to the acquired label information and outputting a corresponding secondary query result;
in one embodiment, the enterprise analysis unit further comprises: and acquiring 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 large database module;
The large database module is used for storing basic information of individuals and enterprises, social credit information and corresponding tag information of the individuals and enterprises.
The beneficial effects of the invention are as follows: the invention sets the big data analysis module, further analyzes and processes the primary query result, extracts the corresponding secondary query result according to the big data analysis result, and can provide the credit information of the secondary query result as a reference and improve the intelligent level of the query system especially aiming at the condition that the credit information of a target person or enterprise in the primary query result is incomplete or not recorded.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a frame construction diagram of the present invention;
fig. 2 is a frame structure diagram of the big data analysis module of the present invention.
Reference numerals:
Input module 1, inquiry 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 scenario.
Referring to fig. 1, there is shown a social credit public query system based on big data, comprising: the system comprises an input module 1, a query module 2, a big data analysis module 3 and a display module 4; wherein,
The input module 1 is used for inputting information to be queried;
the query module 2 is used for carrying out one query from the credit information display 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 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 4 is configured to display a primary query result and a secondary query result corresponding to the primary query result.
The primary query result comprises marking information of an individual or an enterprise, basic information corresponding to the individual or the enterprise and social credit information.
In the above embodiment, the query module is set in the query system to query the target information to be queried input by the user once, and the basic information and the social credit information of the target object are queried from the public credit information display system to be displayed, so that the user can directly know the social credit information of the target object; meanwhile, the big data analysis module 3 can also carry out big data analysis according to the basic information of the target object to acquire the credit information of other objects related to the target object, which is helpful for users to carry out transverse comparison or reference according to the big data analysis result, is helpful for users to further know the credit condition of the target object, and improves the intelligent level of the query system.
The information to be queried input by the input module comprises enterprise names, personal names, keyword information and the like. The output one-time query result can be a single query target or a satisfactory result list, and the list contains satisfactory individuals or enterprises, corresponding basic information, credit information and the like.
In a reference embodiment, the basic information of the individual includes an individual name, location information, marital status, work units, etc., wherein the location information includes a home location or residence;
Basic information of enterprises comprises enterprise names, legal information, registered places, investors, main personnel, total points institutions, change records, litigation information, administrative penalty records, intellectual property rights, registered trademarks, media evaluation and the like;
The social credit information includes credit behaviors, credit behavior times, offensive behaviors, offensive behavior times, social credit scores and the like.
The credit information display system records the basic information of the person or the enterprise and the corresponding social credit information, and the relevant basic information, the social credit information and the like of the person or the enterprise can be searched out from the search engine of the credit information display system by inputting the corresponding target object name.
The credit information display system comprises a government established official national enterprise credit information display system and a personal credit information inquiry system, and can also be an internal credit information inquiry system established by enterprises or enterprise alliances (such as banks, financial institutions, credit institutions and the like); the present application is not limited in detail herein, and may be an existing credit information query system or other credit information query systems.
Aiming at the situation that coverage rate or information is not complete in the existing credit information inquiry system, partial credit information of target individuals or target enterprises is not complete or credit information records are not available, so that the credit situation of the target objects cannot be known; therefore, the application is built based on the existing credit information inquiry system, and the inquiry result is further analyzed and processed by big data on the basis of the existing credit information inquiry system, so that the target object, particularly the target object lacking credit information record, can be effectively analyzed and processed, and the user can be helped to evaluate the target object further according to the big data analysis result to provide 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 obtain a corresponding enterprise tag according to basic information of an enterprise when the primary query result is the enterprise, and 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 obtain a corresponding tag according to personal basic information of the primary query result when the primary query result is personal, and perform big data analysis according to the obtained tag information, and output a corresponding secondary query result.
Aiming at the situation that the query results obtained by the query module 2 from the credit information formula system according to the information to be queried are individuals or enterprises respectively, the large data analysis module 3 is provided with the special enterprise analysis unit 32 and the individual analysis unit 31 to further analyze and process the large data of the different types of primary query results, so that the large data analysis module is beneficial to searching corresponding target data from a large database to analyze according to different types of individuals or enterprises and improving the accuracy of the large data analysis results.
In a reference embodiment, when the primary query result is a person, the personal analysis unit 31 performs further big data analysis according to the basic information and the credit information of the person obtained from the primary query result, firstly performs feature extraction according to the basic information of the person in the primary query result, identifies tag information (such as age, home location, marital status, work unit, etc.) corresponding to the target person, screens out other personal information and corresponding credit information corresponding to the tag information from the big database according to the acquired tag information as analysis samples, performs data screening or cluster analysis and the like on the analysis samples, and acquires reference credit information (such as relevant warning information corresponding to the tag, predictive credit score, analysis sample average credit score, etc.) as an output secondary query result.
In one scenario, only relevant basic information is included in a query result of a target person acquired in the query module, and no record about credit information is included; based on the above-mentioned one-time inquiry result, the personal analysis unit performs feature extraction according to the basic information of the target individual, and obtains the label information of the target individual as "xx year old, residence is YY village, not married, no work unit, etc"; the personal analysis unit is further used for screening out analysis samples corresponding to the tag information from the large database according to the tag information, inputting credit information corresponding to the analysis samples into the cluster analysis model for analysis, and obtaining corresponding prediction credit scores; and meanwhile, searching is carried out according to the obtained tag information, when the information of YY village marked as 'honest demonstration village' by government authorities is searched, the information is used as tag warning information, and is output together with a predicted credit score as a secondary query result, so that a user can comprehensively know and evaluate the information related to the target individual, the user can obtain related reference information from a large database of multiparty information under the condition that the target individual does not have any credit information record, and the width of a credit information reference acquisition channel of the user for the information target individual is improved.
In one embodiment, enterprise analysis unit 32 further includes: the principal information of the enterprise is acquired according to the basic information of the enterprise, the principal information is input to the personal analysis unit 31, the principal is analyzed by the personal analysis unit 31, and a corresponding secondary query result is output.
In a reference embodiment, when the primary query result is an enterprise, the enterprise analysis unit 32 performs further big data analysis according to the basic information and credit information of the target enterprise of the primary query result, firstly performs feature extraction according to the basic information of the enterprise in the primary query result, identifies tag information (such as legal information, registered place, investor information, main personnel information, change records, litigation information, administrative punishment records, intellectual property number, registered trademark number, media evaluation and the like) corresponding to the target enterprise, screens out other personal information and corresponding credit information which are consistent with the tag information from the big database according to the acquired tag information as analysis samples, inputs the basic information of the analysis samples as training samples, outputs the credit information of the analysis samples as training samples, trains the clustering model, acquires a trained clustering model, inputs the tag information of the target enterprise as input parameters into the trained clustering model, and acquires the predicted credit information (credit score) output by the clustering model for display in the secondary query result; and meanwhile, marking the label information with the largest influence on credit score prediction, and displaying in a secondary query result. Meanwhile, when the enterprise analysis unit 32 acquires the enterprise related personal information, the personal information is input to the personal analysis unit 31, the personal analysis unit 31 performs further big data analysis on the related person, and the acquired result is displayed together with the secondary query result. Through the enterprise analysis unit 32, deep large data mining analysis can be performed on the enterprise according to the basic information of the enterprise, and the target enterprise is laterally evaluated based on the data stored in the large database, so that a 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 human ZZ, and inputs the corporate human ZZ as an input parameter thereof into a trained cluster model, and when the corporate human ZZ is detected to be the largest factor affecting credit score (for example, ZZ is a public confidence loss person) through the cluster model, the ZZ is marked and displayed in a secondary query result, so that a user can know that the corporate human ZZ is a confidence loss person even if the credit record of the target enterprise is not available, and the user can use the reference for evaluating the target enterprise.
Meanwhile, the enterprise analysis unit 32 inputs the legal ZZ information into the personal analysis unit 31, and the personal analysis unit 31 performs big data analysis on the legal ZZ information according to the basic information of the legal ZZ, so as to obtain an analysis result related to the individual, and the analysis result is displayed in the secondary query result.
In one embodiment, the system further comprises a large database module;
The large database module is used for storing basic information of individuals and enterprises, social credit information and corresponding tag information of the individuals and enterprises.
The large database module can automatically acquire relevant information of individuals or enterprises from the public data sources, perform data screening, feature extraction and other processes on the acquired information, automatically generate tag information corresponding to the individuals or enterprises, and bind the acquired tag information with the individuals or enterprises. Meanwhile, credit information corresponding to each person or enterprise is recorded in the large database. And related data for displaying the secondary query result.
The query system establishes a perfect big database as a basis of a big data analysis module on the basis of the existing credit information display system, screens and stores massive basic information and credit information of individuals and enterprises in a classified manner, and provides guarantee for the accuracy of big data analysis of the query system.
It should be noted that, in each embodiment of the present invention, each functional unit/module may be integrated in one processing unit/module, or each unit/module may exist alone physically, or two or more units/modules may be integrated in one unit/module. The integrated units/modules described above may be implemented either in hardware or in software functional units/modules.
From the description of the embodiments above, it will be apparent to those skilled in the art that the embodiments described herein may be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For a hardware implementation, the 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 flow of an embodiment may be accomplished by a computer program to instruct the associated hardware. When implemented, the above-described programs may be stored in or transmitted 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 are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media 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 for illustrating the technical solution of the present invention, and not for limiting the scope of the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (3)
1. A social credit publicity query system based on big data, comprising: the system 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 queried;
The query module is used for carrying out one-time query from the credit information display system according to the information to be queried and outputting a corresponding one-time query 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 a primary query result and a secondary query result corresponding to the primary query result;
the primary query result comprises marking information of an individual or an enterprise, and basic information and social credit information corresponding to the individual or the enterprise;
the big data analysis module comprises a personal analysis unit and an enterprise analysis unit;
The enterprise analysis unit is used for acquiring corresponding enterprise labels according to the basic information of the enterprise when the primary query result is the enterprise, analyzing big data according to the acquired label information and outputting the corresponding secondary query result; comprising the following steps:
when the primary query result is an enterprise, the enterprise analysis unit performs further big data analysis according to basic information and credit information of the target enterprise of the primary query result, firstly performs feature extraction according to the basic information of the enterprise in the primary query result, identifies tag information corresponding to the target enterprise, wherein the tag information comprises legal information, registered places, investor information, main personnel information, change records, litigation information, administrative punishment records, intellectual property number, registered trademark number and media evaluation, screens out other personal information and corresponding credit information which are consistent with the tag information from a big database according to the acquired tag information, takes the basic information of the analysis sample as a training sample, outputs the credit information of the analysis sample as a training sample, trains a clustering model, acquires a trained clustering model, inputs the tag information of the target enterprise as an input parameter into the trained clustering model, and acquires predicted credit information output by the clustering model for display in the secondary query result; meanwhile, marking label information with the largest influence on credit score prediction, and displaying in a secondary query result; meanwhile, after the enterprise analysis unit acquires the enterprise related personal information, the personal information is input into the personal analysis unit, the personal analysis unit carries out further big data analysis on the related person, and the acquired result is displayed in the secondary query result;
The personal analysis unit is used for acquiring corresponding labels according to personal basic information of the primary query result when the primary query result is personal, analyzing big data according to the acquired label information and outputting a corresponding secondary query result; comprising the following steps:
When the primary query result is an individual, the personal analysis unit performs further big data analysis according to the basic information and the credit information of the individual obtained from the primary query result, firstly performs feature extraction according to the basic information of the individual in the primary query result, identifies the tag information corresponding to the target individual, screens out other personal information and corresponding credit information which are consistent with the tag information from the big database according to the acquired tag information as analysis samples, performs data screening or cluster analysis on the analysis samples, and acquires the reference credit information as an output secondary query result.
2. The big data based social credit publicity query system of claim 1, wherein said enterprise analysis unit further comprises: and acquiring 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.
3. The big data based social credit publicity query system of claim 2, wherein said system further comprises a big database module;
The large 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)
| Publication number | Priority date | Publication date | Assignee | Title |
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| 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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Patent Citations (4)
| 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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