CN110852725A - Project declaration system based on big data - Google Patents
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Abstract
The invention discloses a project declaration system based on big data, which comprises a data acquisition terminal, a data security module, a server, a data analysis processing module, an auditing module, a feedback module and a declaration module. Has the advantages that: by using the data encryption module, project information applied by a user can be protected, the project information of the user is prevented from being stolen, economic loss is prevented, and by using the data compression module, the storage space of data can be reduced, and the cost of file storage is reduced. Through using the data analysis processing module, the detailed specific situation of the assessment project can be scientifically specified, randomness, blindness and one-sidedness are avoided, the quality and the level of project assessment are high, repeated project establishment is avoided, the novelty and the advancement of the project are guaranteed, and the auditing module and the feedback module are arranged, so that the audited data are more accurate, and the success rate of reporting is increased.
Description
Technical Field
The invention relates to the technical field of project declaration, in particular to a project declaration system based on big data.
Background
The modern society is an information society era and a big data era; with continuous development and progress of information technologies such as internet, internet of things, cloud computing, artificial intelligence and the like and computer industry, data processing becomes a problem to be solved urgently; therefore, in the context of big data, how to efficiently obtain useful information from a database has become a major concern of enterprises and scientific research units, and the key technology involved in the work is data analysis and data mining technology; in summary, the need for data processing presents both opportunities and a series of challenges to data mining technologies.
The project information has the characteristics of unstructured data types, huge data volume and the like, the data source is often trans-regional data accumulated for many years, and the processing time of a common machine and an algorithm is long. The current project evaluation adopts an expert scoring mode, and the main contents of the evaluation comprise: evaluating the necessity and feasibility of project establishment; evaluating by taking the current development situation, the technical condition and the research level of the project at home and abroad as indexes; evaluating the project research and development contents, the technical process routes and the implementation schemes; evaluating the capability of the project undertaking units, and evaluating the scientific research capability of the undertaking units, the professional level of talents and the management capability of scientific research equipment and projects; evaluating the implementation condition of project expenses, and evaluating the fund source, self-funded fund, government supporting fund and amount.
Because project information has the characteristics of big data complexity, different knowledge of experts, deviation in knowledge field and certain subjective consciousness, a declaration program also has complexity, and declaration conditions have ambiguity, the conclusion obtained by project establishment evaluation only by expert scoring is often insufficient in scientific basis, and the project optimization consensus is difficult to form. Thus, there will be some randomness, blindness and sidedness in expert review, resulting in low quality and level of project evaluation and imperfect project expert review mechanism. The comprehensiveness and credibility of expert project scoring is to be further enhanced.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a project declaration system based on big data, so as to overcome the technical problems in the prior related art.
Therefore, the invention adopts the following specific technical scheme:
a project declaration system based on big data comprises a data acquisition terminal, a data security module, a server, a data analysis processing module, an auditing module, a feedback module and a declaration module;
the data acquisition terminal is used for acquiring related information of an enterprise project, generating declaration data and uploading the declaration data to the data security module;
the data security module is used for encrypting and compressing the acquired declaration data to generate primary processing data and uploading the primary processing data to the server;
the server is used for exchanging the received preliminary processing data with the data analysis processing module;
the data analysis processing module is used for performing data processing analysis on the acquired preliminary processing data to generate processing data and uploading the processing data to the auditing module;
the auditing module is used for auditing the acquired processing data and uploading the audited data to the feedback module;
the feedback module is used for feeding back the audited data to the user and providing a data basis for the declaration module;
the declaration module is used for declaring the project;
the data security module comprises a data encryption module, a data compression module and a data uploading module;
the data encryption module is used for encrypting the acquired declaration data;
the data compression module is used for compressing the encrypted declaration data;
the data uploading module is used for uploading the compressed declaration data to the server.
Further, the enterprise project related information comprises project establishment application data, current research hotspot data, supporting direction data, investigation feedback suggestion information data, project application unit comprehensive strength information data and historical project information data;
the current research hotspot data comprise latest development direction data and hotspot information data;
the supporting direction data comprises national policy supporting direction information data set local government industry development direction information data;
the historical project information data comprises historical similar project establishment condition information data, historical established project construction condition information data and historical project effect information data.
Further, the data encryption module is configured to encrypt the obtained declaration data, and includes the following steps:
configuring corresponding first encryption suites aiming at different declaration data;
sending HTTPS request content including a uniform resource identifier, URI, and a request header/message body;
receiving the HTTPS request content, and determining a second encryption suite corresponding to the data acquisition terminal in the first encryption suite according to the Uniform Resource Identifier (URI) in the HTTPS request content;
comparing the security degree of the first encryption suite with the security degree of the second encryption suite, and if the security degree of the first encryption suite is smaller than the security degree of the second encryption suite, sending a renegotiation request;
and receiving the renegotiation request and renegotiating the first encryption suite.
Further, the data compression module is configured to compress the encrypted declaration data, and includes the following steps:
acquiring encrypted declaration data and an initial acquisition time point of the encrypted declaration data, and setting the type of a fitting curve of the encrypted declaration data;
acquiring an initial feasible region of the encrypted declaration data according to the fitting curve;
acquiring first encrypted declaration data of a set time interval after the initial acquisition time point, and acquiring a first feasible region of the first encrypted declaration data according to the fitting curve;
step four, judging whether an intersection exists between the initial feasible region and the first feasible region;
if an intersection exists, taking the intersection as an initial feasible domain, taking the first encrypted declaration data as initial measurement data, and executing a third step;
if the intersection does not exist, obtaining coordinate values in the initial feasible region, wherein the coordinate values are used as coefficients of a fitting curve, storing the coordinate values and the encrypted declaration data obtained at the initial time point in the first step, using the first encrypted declaration data as the encrypted declaration data, and executing the first step.
Furthermore, the data analysis processing module comprises a decryption reduction module, a data comparison module, a weight analysis module, a data duplication checking module and a data integration module;
the decryption restoration module is used for decrypting the received preliminary processing data and restoring the received preliminary processing data into the declaration data;
the data comparison module is used for comparing the declaration data with the enterprise project related information;
the weight analysis module is used for distinguishing the comparison results of the declaration data, project establishment application data, current research hotspot data, support direction data, investigation feedback suggestion information data, project application unit comprehensive strength information data and historical project information data according to the importance degree, and obtaining evaluation of the project establishment application and an establishment suggestion report according to the weight analysis results;
the data duplication checking module is used for avoiding repeated project establishment and judging the novelty and the advancement of the project;
the data integration module is used for performing full data integration or historical data integration on the declaration data of the current day and the integrated data of the previous day to obtain data integrated on the current day, and storing the data in an integrated data storage library.
Further, the data comparison module for comparing the declaration data with the information related to the enterprise project further includes the following steps:
acquiring the latest development direction, hotspot information and related project establishment application data of project related technologies, processing the latest development direction, hotspot information and related project establishment application data to obtain current research hotspot data, and comparing the current research hotspot data with the declaration data to obtain a first result;
acquiring information of a national policy support direction and a local government industry development direction, processing the information to obtain support direction data, and comparing the support direction data with the declaration data to obtain a second result;
acquiring comprehensive strength information of a competent department, on-site industry investigation feedback suggestion information and comprehensive strength information of a project application unit, processing the comprehensive strength information and outputting a third result embodied in a data form;
acquiring similar project establishment conditions and established project construction conditions and effects of the departments in the past, processing the similar project establishment conditions and established project construction conditions in the past to obtain a vector space set, and comparing the vector space set with the declaration data to obtain a fourth result.
Further, the data duplication checking module is used for avoiding repeated project establishment, and the judgment of the novelty and the advancement of the project further comprises the following steps:
collecting related files of policies, notices and opinions for sorting the project classes by utilizing a web crawler technology;
according to the key data obtained by classifying, sorting and refining the related files of the project experts, project duplication checking index data are formed, and project index design is completed;
storing the project duplicate checking index data into a project index library and a project management library to generate a duplicate checking rule table;
acquiring data of enterprise basic information data, enterprise credit investigation data and project data by acquiring enterprise big data and accessing an industrial and commercial interface;
and matching the repeated content of the project through the project management library and the project index library according to the duplication checking rule table and by combining the basic information of the enterprise, the credit investigation data of the enterprise and the project information item by item to compare whether the project meets the standard condition of the duplication checking rule table index.
Further, the data integration module is configured to perform full data integration or historical data integration on the declaration data of the current day and the integrated data of the previous day to obtain data integrated on the current day, and store the data in the integrated data storage library, and further includes the following steps:
reading the transit data of the current day and the integrated data of the previous day by using a second distributed data set generation module, and generating a corresponding Spark RDD on a distributed node;
reading the Spark RDD generated by the second distributed data set generation module by using a full data integration module, correspondingly performing increase, deletion and change operations on data with the same key value in the Spark RDD of the previous day according to the increase, deletion and change identifiers in the transfer data, and after the processing is finished, forming the transfer data Spark RDD and storing the transfer data Spark RDD into an integrated data storage library;
and reading the transfer data Spark RDD of the current day by using a historical data integration module, correspondingly processing the data with the same key value in the integration data Spark RDD of the previous day according to the addition, deletion and modification marks in the transfer data, and storing the processed data into an integration data storage library.
Furthermore, the auditing module comprises a department auditing module, a financial auditing module and a manpower auditing module;
wherein the department audit module is used for reviewing the effect of the project;
the financial auditing module is used for reviewing the economic value of the project;
the manpower auditing module is used for reviewing the manpower consumption of the project.
Further, the feedback module comprises a project progress module and an exchange module;
the project progress module is used for recording project progress;
the communication module is used for inquiring and communicating with a user.
The invention has the beneficial effects that: by using the data encryption module, the project information applied by the user can be protected, and the project information of the user is prevented from being stolen to cause economic loss. By using the data compression module, the storage space of data can be reduced, and the cost of file storage is reduced. Through using the data analysis processing module to can the meticulous concrete condition of aassessment project of scientific specification, avoid haphazardness, blind nature and one-sidedness, and then make the quality and the level of project aassessment higher, avoid the repeated project establishment of project, guarantee novelty and the advance of project. And by arranging the auditing module and the feedback module, the audited data is more accurate, and the reporting success rate is increased.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic diagram of a big data based project declaration system, in accordance with an embodiment of the present invention.
In the figure:
1. a data acquisition terminal; 2. a data security module; 201. a data encryption module; 202. a data compression module; 203. a data uploading module; 3. a server; 4. a data analysis processing module; 401. a decryption restoration module; 402. a data comparison module; 403. a weight analysis module; 404. a data duplicate checking module; 405. a data integration module; 5. an audit module; 501. a department audit module; 502. a financial auditing module; 503. a human audit module; 6. a feedback module; 601. a project progress module; 602. an alternating current module; 7. and a reporting module.
Detailed Description
For further explanation of the various embodiments, the drawings which form a part of the disclosure and which are incorporated in and constitute a part of this specification, illustrate embodiments and, together with the description, serve to explain the principles of operation of the embodiments, and to enable others of ordinary skill in the art to understand the various embodiments and advantages of the invention, and, by reference to these figures, reference is made to the accompanying drawings, which are not to scale and wherein like reference numerals generally refer to like elements.
According to an embodiment of the present invention, a big data based project declaration system is provided.
Referring to the drawings and the detailed description, the invention is further described, as shown in fig. 1, a project declaration system based on big data according to an embodiment of the invention includes a data acquisition terminal 1, a data security module 2, a server 3, a data analysis processing module 4, an auditing module 5, a feedback module 6 and a declaration module 7;
the data acquisition terminal 1 is used for acquiring enterprise project related information, generating declaration data and uploading the declaration data to the data security module 2;
the data security module 2 is configured to encrypt and compress the obtained declaration data to generate primary processing data, and upload the primary processing data to the server 3;
the server 3 is configured to perform data exchange between the received preliminary processing data and the data analysis processing module 4;
the data analysis processing module 4 is configured to perform data processing analysis on the acquired preliminary processing data to generate processing data, and upload the processing data to the auditing module 5;
the auditing module 5 is used for auditing the acquired processing data and uploading the audited data to the feedback module 6;
the feedback module 6 is used for feeding back the audited data to the user and providing a data basis for the declaration module 7;
the declaration module 7 is used for declaring projects;
the data security module 2 comprises a data encryption module 201, a data compression module 202 and a data uploading module 203;
the data encryption module 201 is configured to encrypt the obtained declaration data;
the data compression module 202 is configured to compress the encrypted declaration data;
the data uploading module 203 is configured to upload the compressed declaration data to the server 3.
In one embodiment, the enterprise project related information includes project establishment application data, current research hotspot data, support direction data, review feedback suggestion information data, project application unit comprehensive strength information data, and historical project information data;
the current research hotspot data comprise latest development direction data and hotspot information data;
the supporting direction data comprises national policy supporting direction information data set local government industry development direction information data;
the historical project information data comprises historical similar project establishment condition information data, historical established project construction condition information data and historical project effect information data.
In one embodiment, the data encryption module 201 is configured to encrypt the acquired declaration data, and includes the following steps:
configuring corresponding first encryption suites aiming at different declaration data;
sending HTTPS request content including a uniform resource identifier, URI, and a request header/message body;
receiving the HTTPS request content, and determining a second encryption suite corresponding to the data acquisition terminal 1 in the first encryption suite according to the Uniform Resource Identifier (URI) in the HTTPS request content;
comparing the security degree of the first encryption suite with the security degree of the second encryption suite, and if the security degree of the first encryption suite is smaller than the security degree of the second encryption suite, sending a renegotiation request;
and receiving the renegotiation request and renegotiating the first encryption suite.
In one embodiment, the data compression module 202 is configured to compress the encrypted declaration data, and includes the following steps:
acquiring encrypted declaration data and an initial acquisition time point of the encrypted declaration data, and setting the type of a fitting curve of the encrypted declaration data;
acquiring an initial feasible region of the encrypted declaration data according to the fitting curve;
acquiring first encrypted declaration data of a set time interval after the initial acquisition time point, and acquiring a first feasible region of the first encrypted declaration data according to the fitting curve;
step four, judging whether an intersection exists between the initial feasible region and the first feasible region;
if an intersection exists, taking the intersection as an initial feasible domain, taking the first encrypted declaration data as initial measurement data, and executing a third step;
if the intersection does not exist, obtaining coordinate values in the initial feasible region, wherein the coordinate values are used as coefficients of a fitting curve, storing the coordinate values and the encrypted declaration data obtained at the initial time point in the first step, using the first encrypted declaration data as the encrypted declaration data, and executing the first step.
In one embodiment, the data analysis processing module 4 includes a decryption restoration module 401, a data comparison module 402, a weight analysis module 403, a data duplication checking module 404 and a data integration module 405;
the decryption and restoration module 401 is configured to decrypt the received preliminary processing data and restore the received preliminary processing data to the declaration data;
the data comparison module 402 is configured to compare the declaration data with the information related to the enterprise project;
the weight analysis module 403 is configured to distinguish results of comparison between the declaration data and the project establishment application data, the current research hotspot data, the support direction data, the review feedback recommendation information data, the project application unit comprehensive strength information data, and the historical project information data according to importance degrees, and obtain an evaluation of the project establishment application and an establishment recommendation report according to a weight analysis result;
the data duplication checking module 404 is used for avoiding repeated project establishment and judging novelty and advancement of the project;
the data integration module 405 is configured to perform full data integration or historical data integration on the declaration data of the current day and the integrated data of the previous day, obtain data after current day integration, and store the data in an integrated data storage library.
In one embodiment, the data comparison module 402 for comparing the declaration data with the information related to the enterprise project further comprises the steps of:
acquiring the latest development direction, hotspot information and related project establishment application data of project related technologies, processing the latest development direction, hotspot information and related project establishment application data to obtain current research hotspot data, and comparing the current research hotspot data with the declaration data to obtain a first result;
acquiring information of a national policy support direction and a local government industry development direction, processing the information to obtain support direction data, and comparing the support direction data with the declaration data to obtain a second result;
acquiring comprehensive strength information of a competent department, on-site industry investigation feedback suggestion information and comprehensive strength information of a project application unit, processing the comprehensive strength information and outputting a third result embodied in a data form;
in an embodiment, the data duplication checking module 404 is configured to avoid repeated project establishment and judge novelty and advancement of the project, and further includes the following steps:
collecting related files of policies, notices and opinions for sorting the project classes by utilizing a web crawler technology;
according to the key data obtained by classifying, sorting and refining the related files of the project experts, project duplication checking index data are formed, and project index design is completed;
storing the project duplicate checking index data into a project index library and a project management library to generate a duplicate checking rule table;
acquiring data of enterprise basic information data, enterprise credit investigation data and project data by acquiring enterprise big data and accessing an industrial and commercial interface;
and matching the repeated content of the project through the project management library and the project index library according to the duplication checking rule table and by combining the basic information of the enterprise, the credit investigation data of the enterprise and the project information item by item to compare whether the project meets the standard condition of the duplication checking rule table index.
In one embodiment, the data integration module 405 is configured to perform full data integration or historical data integration on the declaration data of the current day and the integration data of the previous day, so as to obtain data after current day integration, and store the data in the integration data repository, further including the following steps:
reading the transit data of the current day and the integrated data of the previous day by using a second distributed data set generation module, and generating a corresponding Spark RDD on a distributed node;
reading the Spark RDD generated by the second distributed data set generation module by using a full data integration module, correspondingly performing increase, deletion and change operations on data with the same key value in the Spark RDD of the previous day according to the increase, deletion and change identifiers in the transfer data, and after the processing is finished, forming the transfer data Spark RDD and storing the transfer data Spark RDD into an integrated data storage library;
and reading the transfer data Spark RDD of the current day by using a historical data integration module, correspondingly processing the data with the same key value in the integration data Spark RDD of the previous day according to the addition, deletion and modification marks in the transfer data, and storing the processed data into an integration data storage library.
In one embodiment, the auditing module 5 includes a department auditing module 501, a financial auditing module 502, and a human auditing module 503;
wherein, the department auditing module 501 is used for reviewing the effect of the project;
the financial auditing module 502 is used to review the economic value of a project;
the human audit module 503 is used to review the human consumption of the project.
In one embodiment, the feedback module 6 includes a project schedule module 601 and a communication module 602;
the project progress module 601 is used for recording project progress;
the communication module 602 is used for inquiring and communicating with a user.
In summary, according to the above technical solution of the present invention, by using the data encryption module 201, the item information applied by the user can be protected, and the item information of the user is prevented from being stolen, which causes economic loss. By using the data compression module 202, the storage space of data can be reduced, and the cost of file storage is reduced. Through using data analysis processing module 4 to can the meticulous concrete condition of aassessment project of scientific specification, avoid haphazardness, blind nature and one-sidedness, and then make the quality and the level of project aassessment higher, avoid the repeated project establishment of project, guarantee novelty and the advance of project. And by arranging the auditing module 5 and the feedback module 6, the audited data is more accurate, and the reporting success rate is increased.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A project declaration system based on big data is characterized by comprising a data acquisition terminal (1), a data security module (2), a server (3), a data analysis processing module (4), an auditing module (5), a feedback module (6) and a declaration module (7);
the data acquisition terminal (1) is used for acquiring enterprise project related information, generating declaration data and uploading the declaration data to the data security module (2);
the data security module (2) is used for encrypting and compressing the acquired declaration data to generate primary processing data and uploading the primary processing data to the server (3);
the server (3) is used for exchanging the received preliminary processing data with the data analysis processing module (4);
the data analysis processing module (4) is used for performing data processing analysis on the acquired preliminary processing data to generate processing data, and uploading the processing data to the auditing module (5);
the auditing module (5) is used for auditing the acquired processing data and uploading the audited data to the feedback module (6);
the feedback module (6) is used for feeding the audited data back to the user and providing a data basis for the declaration module (7);
the declaration module (7) is used for declaring the project;
the data security module (2) comprises a data encryption module (201), a data compression module (202) and a data uploading module (203);
the data encryption module (201) is used for encrypting the acquired declaration data;
the data compression module (202) is used for compressing the encrypted declaration data;
the data uploading module (203) is used for uploading the compressed declaration data to the server (3).
2. The big data-based project declaration system of claim 1, wherein the enterprise project related information includes project establishment application data, current research hotspot data, support direction data, review feedback suggestion information data, project application unit comprehensive strength information data, and historical project information data;
the current research hotspot data comprise latest development direction data and hotspot information data;
the supporting direction data comprises national policy supporting direction information data set local government industry development direction information data;
the historical project information data comprises historical similar project establishment condition information data, historical established project construction condition information data and historical project effect information data.
3. The big data based project declaration system of claim 1, wherein the data encryption module (201) is configured to encrypt the declaration data obtained by the data encryption module, and comprises the following steps:
configuring corresponding first encryption suites aiming at different declaration data;
sending HTTPS request content including a uniform resource identifier, URI, and a request header/message body;
receiving the HTTPS request content, and determining a second encryption suite corresponding to the data acquisition terminal (1) in the first encryption suite according to the Uniform Resource Identifier (URI) in the HTTPS request content;
comparing the security degree of the first encryption suite with the security degree of the second encryption suite, and if the security degree of the first encryption suite is smaller than the security degree of the second encryption suite, sending a renegotiation request;
and receiving the renegotiation request and renegotiating the first encryption suite.
4. The big data based project declaration system of claim 1, wherein the data compression module (202) is configured to compress the declaration data after encryption, and comprises the following steps:
acquiring encrypted declaration data and an initial acquisition time point of the encrypted declaration data, and setting the type of a fitting curve of the encrypted declaration data;
acquiring an initial feasible region of the encrypted declaration data according to the fitting curve;
acquiring first encrypted declaration data of a set time interval after the initial acquisition time point, and acquiring a first feasible region of the first encrypted declaration data according to the fitting curve;
step four, judging whether an intersection exists between the initial feasible region and the first feasible region;
if an intersection exists, taking the intersection as an initial feasible domain, taking the first encrypted declaration data as initial measurement data, and executing a third step;
if the intersection does not exist, obtaining coordinate values in the initial feasible region, wherein the coordinate values are used as coefficients of a fitting curve, storing the coordinate values and the encrypted declaration data obtained at the initial time point in the first step, using the first encrypted declaration data as the encrypted declaration data, and executing the first step.
5. The big data-based project declaration system of claim 1, wherein the data analysis processing module (4) comprises a decryption restoration module (401), a data comparison module (402), a weight analysis module (403), a data duplication checking module (404) and a data integration module (405);
the decryption restoration module (401) is configured to decrypt the received preliminary processing data and restore the received preliminary processing data to the declaration data;
the data comparison module (402) is used for comparing the declaration data with the enterprise project related information;
the weight analysis module (403) is used for distinguishing results of comparison between the declaration data and project establishment application data, current research hotspot data, support direction data, investigation feedback recommendation information data, project application unit comprehensive strength information data and historical project information data according to importance degrees, and obtaining evaluation of the project establishment application and establishment recommendation reports according to weight analysis results;
the data duplication checking module (404) is used for avoiding repeated project establishment and judging the novelty and the advancement of the project;
the data integration module (405) is used for performing full data integration or historical data integration on the declaration data of the current day and the integrated data of the previous day to obtain data integrated on the current day, and storing the data in an integrated data storage library.
6. The big-data based project declaration system of claim 5, wherein the data comparison module (402) for comparing the declaration data with the enterprise project related information further comprises the steps of:
acquiring the latest development direction, hotspot information and related project establishment application data of project related technologies, processing the latest development direction, hotspot information and related project establishment application data to obtain current research hotspot data, and comparing the current research hotspot data with the declaration data to obtain a first result;
acquiring information of a national policy support direction and a local government industry development direction, processing the information to obtain support direction data, and comparing the support direction data with the declaration data to obtain a second result;
acquiring comprehensive strength information of a competent department, on-site industry investigation feedback suggestion information and comprehensive strength information of a project application unit, processing the comprehensive strength information and outputting a third result embodied in a data form;
acquiring similar project establishment conditions and established project construction conditions and effects of the departments in the past, processing the similar project establishment conditions and established project construction conditions in the past to obtain a vector space set, and comparing the vector space set with the declaration data to obtain a fourth result.
7. The big data based project declaration system of claim 5, wherein the data duplication checking module (404) is configured to avoid project duplicate establishment, and the determining novelty and advancement of the project further comprises the steps of:
collecting related files of policies, notices and opinions for sorting the project classes by utilizing a web crawler technology;
according to the key data obtained by classifying, sorting and refining the related files of the project experts, project duplication checking index data are formed, and project index design is completed;
storing the project duplicate checking index data into a project index library and a project management library to generate a duplicate checking rule table;
acquiring data of enterprise basic information data, enterprise credit investigation data and project data by acquiring enterprise big data and accessing an industrial and commercial interface;
and matching the repeated content of the project through the project management library and the project index library according to the duplication checking rule table and by combining the basic information of the enterprise, the credit investigation data of the enterprise and the project information item by item to compare whether the project meets the standard condition of the duplication checking rule table index.
8. The big-data based project declaration system of claim 5, wherein the data integration module (405) is configured to perform a full data integration or a historical data integration on the declaration data of the current day and the integration data of the previous day, so as to obtain the data after the current day integration, and store the data in the integration data repository, further comprising the following steps:
reading the transit data of the current day and the integrated data of the previous day by using a second distributed data set generation module, and generating a corresponding Spark RDD on a distributed node;
reading the Spark RDD generated by the second distributed data set generation module by using a full data integration module, correspondingly performing increase, deletion and change operations on data with the same key value in the Spark RDD of the previous day according to the increase, deletion and change identifiers in the transfer data, and after the processing is finished, forming the transfer data Spark RDD and storing the transfer data Spark RDD into an integrated data storage library;
and reading the transfer data Spark RDD of the current day by using a historical data integration module, correspondingly processing the data with the same key value in the integration data Spark RDD of the previous day according to the addition, deletion and modification marks in the transfer data, and storing the processed data into an integration data storage library.
9. A big data based project declaration system as claimed in claim 1, wherein said audit module (5) comprises a department audit module (501), a financial audit module (502) and a human audit module (503);
wherein the department review module (501) is configured to review the effects of the project;
the financial auditing module (502) is used for reviewing the economic value of a project;
the human audit module (503) is used for reviewing human consumption of the project.
10. A big data based project declaration system as claimed in claim 1, wherein said feedback module (6) comprises a project progress module (601) and an exchange module (602);
wherein, the project progress module (601) is used for recording project progress;
the communication module (602) is used for inquiring and communicating with a user.
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| CN201911135368.8A CN110852725A (en) | 2019-11-19 | 2019-11-19 | Project declaration system based on big data |
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| CN201911135368.8A CN110852725A (en) | 2019-11-19 | 2019-11-19 | Project declaration system based on big data |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111798080A (en) * | 2020-04-27 | 2020-10-20 | 汕头市高博电子科技有限公司 | Help item data management method and system |
| CN112749379A (en) * | 2021-02-20 | 2021-05-04 | 上海理工大学 | Deep learning-based project declaration system and method |
| CN112801629A (en) * | 2021-02-04 | 2021-05-14 | 江西清能高科技术有限公司 | Science and technology innovation platform project declaration method and system based on multi-level encryption |
| CN113095647A (en) * | 2021-04-01 | 2021-07-09 | 中国汽车技术研究中心有限公司 | Vehicle inspection system |
| CN113421026A (en) * | 2021-07-19 | 2021-09-21 | 首都医科大学附属北京儿童医院 | Hospital scientific research project application management method and system |
| CN113888142A (en) * | 2021-11-15 | 2022-01-04 | 常州市科技资源统筹服务中心(常州市科技情报研究所) | Project intelligent management method and system for reporting enterprise information |
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2019
- 2019-11-19 CN CN201911135368.8A patent/CN110852725A/en not_active Withdrawn
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111798080A (en) * | 2020-04-27 | 2020-10-20 | 汕头市高博电子科技有限公司 | Help item data management method and system |
| CN112801629A (en) * | 2021-02-04 | 2021-05-14 | 江西清能高科技术有限公司 | Science and technology innovation platform project declaration method and system based on multi-level encryption |
| CN112749379A (en) * | 2021-02-20 | 2021-05-04 | 上海理工大学 | Deep learning-based project declaration system and method |
| CN113095647A (en) * | 2021-04-01 | 2021-07-09 | 中国汽车技术研究中心有限公司 | Vehicle inspection system |
| CN113095647B (en) * | 2021-04-01 | 2023-01-06 | 中国汽车技术研究中心有限公司 | Vehicle inspection system |
| CN113421026A (en) * | 2021-07-19 | 2021-09-21 | 首都医科大学附属北京儿童医院 | Hospital scientific research project application management method and system |
| CN113888142A (en) * | 2021-11-15 | 2022-01-04 | 常州市科技资源统筹服务中心(常州市科技情报研究所) | Project intelligent management method and system for reporting enterprise information |
| CN113888142B (en) * | 2021-11-15 | 2022-04-19 | 常州市科技资源统筹服务中心(常州市科技情报研究所) | Project intelligent management method and system for reporting enterprise information |
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