CN113641660A - Big data analysis system for retired soldier - Google Patents
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Abstract
The invention relates to a big data analysis system for retired soldiers, which comprises a data resource module, a resource analysis module and a theme analysis module; the data resource module is used for displaying a catalogue of retired soldier data and providing an entrance for acquiring corresponding retired soldier data according to the catalogue, the catalogue comprises internal data, external data and service data, the internal data is data acquired from a retired soldier management system, the external data is data acquired from a service system and an industry mechanism system, and the service data is data generated by a big data analysis system; the resource analysis module is used for carrying out statistical analysis of different dimensions on the retired soldier data to obtain statistical analysis results and displaying the statistical analysis results; the theme analysis module comprises a petition visiting unit, an employment entrepreneurship unit and a pacifying and treating unit and is used for carrying out data analysis under different themes. The invention can effectively solve the problems that retired soldier data are difficult to utilize and the application value of the data is difficult to exert.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a big data analysis system for retired soldiers.
Background
The development of personnel management work of retired soldiers mainly depends on basic data of the retired soldiers, but the basic data are dispersed in all relevant departments, and the department systems lack interconnection, so that a retired soldier information system for personnel management work lacks data support and is difficult to apply and optimize. Moreover, various data of retired soldiers have the problems of incompleteness, inaccuracy, immobility, non authority and the like, the data quality is low, the standardization is not strong, the data value is difficult to be effectively played, and the utilization rate of data resources is low.
Disclosure of Invention
The invention aims to overcome at least one defect (deficiency) of the prior art and provides a retired soldier big data analysis system which is used for solving the problems that retired soldier data are difficult to utilize and exert data application value.
The technical scheme adopted by the invention is as follows:
a big data analysis system for retired soldiers comprises a data resource module, a resource analysis module and a theme analysis module;
the data resource module is used for displaying a catalogue of retired soldier data and providing an entrance for acquiring the retired soldier data according to the catalogue, wherein the catalogue comprises internal data, external data and service data, the internal data is data acquired from a retired soldier management system, the external data is data acquired from a service system and an industry mechanism system, and the service data is data generated by the big data analysis system;
the resource analysis module is used for carrying out statistical analysis of different dimensions on the retired soldier data to obtain a statistical analysis result and displaying the statistical analysis result;
the theme analysis module comprises a petition visiting unit, an employment entrepreneurship unit and a pacifying and treating unit;
the petition visiting unit is used for extracting and analyzing the data of the refuge visitors from the data of the retired soldiers to obtain the statistical information of the refuge visitors to be visited and displaying the statistical information;
the employment startup unit is used for extracting and analyzing the data of the retired soldiers of the employment startup from the retired soldier data to obtain the statistical information of the retired soldiers of the employment startup and displaying the statistical information;
and the preferential treatment unit is used for extracting and analyzing the data of the retired soldier who is a preferential object from the retired soldier data to obtain the statistical information of the preferential object and displaying the statistical information.
Further, the external data acquired from the government affair system comprises safety data, civil administration data, judicial data, human-society data, health data, market supervision data and natural resource data of retired soldiers; the external data acquired from the industry institution system includes medical data, educational data, housing data, bank data, and travel data.
Further, the theme analysis module further comprises an integral display unit; the integral display unit is used for determining longitude and latitude information of each retired soldier and a place name address and an administrative area to which the longitude and latitude information belongs according to the household registration information in the safety data, forming dotting layers of different levels according to the longitude and latitude information and administrative areas of different levels according to the place name address and the administrative area, combining the dotting layers of different levels with a map to form a retired soldier distribution situation map of the administrative areas of different levels, and displaying the distribution situation map.
Further, the integral display unit is further configured to count the number of retired soldiers in different levels in each administrative area according to an administrative area to which the longitude and latitude information of each retired soldier belongs, obtain a retired soldier number statistical list in the administrative areas in different levels, and synchronously display the number statistical list in the administrative areas in the same level as the retired soldier distribution graph when the distribution graph is displayed.
Further, the theme analysis module further comprises a person-document unit; the one-person one-file unit is used for extracting personal data of one retired military person from the retired military person data, arranging the personal data into personal information and displaying the personal information, wherein the personal information comprises basic information, household registration information, social security information, family information, education background, military service information, information of visiting and visiting, living information, visiting and visiting information, honor information, working information, tax payment information, preferential treatment information, disability information, poverty information, arrangement information, death information and legal person information.
Further, the one-person one-file unit is further used for analyzing the image of the retired soldier according to the personal data to obtain an image label of the retired soldier, the image label is synchronously displayed when the personal information is displayed, the type of the image label comprises basic features, a credit condition, a reward and punishment condition, an education condition, a working condition and a placement condition, and the basic features comprise a plurality of ages, sexes, native countries, marital states and political appearances.
Further, the resource analysis module is specifically configured to determine the number of selectable fields according to the selected statistical manner, determine analysis dimensions according to the selected fields, perform statistical analysis of different dimensions on the retired soldier data according to the determined analysis dimensions, obtain statistical analysis results, and display the statistical analysis results, where the fields include a plurality of personnel categories, visiting and visiting months, geographical distribution, political aspects, household categories, age distribution, annual income, service years, retirement manners, social insurance, enjoying, and cultural degrees.
Furthermore, the retired soldier big data analysis system further comprises a data service module, wherein the data service module comprises one or more of a data governance unit, a data analysis unit and a data sharing unit;
the data management unit is used for carrying out classified carding, cleaning and completion on the retired soldier data, configuring a data rule of the retired soldier data, searching and issuing problem data which do not accord with the data rule from the retired soldier data, and generating a data quality report according to the problem data;
the data analysis unit is used for extracting the data of the retired soldier who visits and visits from the retired soldier data and performing data collision analysis to determine the difficult problem of the retired soldier who visits and visits, and/or is used for extracting the data of the retired soldier who enters employment and entrepreneurship from the retired soldier data and performing data collision analysis to obtain a sentry matching analysis model and/or a special skill training model, and/or is used for extracting the data of the retired soldier who applies to the application allowance from the retired soldier data and performing data collision analysis to obtain the result data of the illegal application allowance, and early warning information is pushed according to the result data;
the data sharing unit is used for sharing the retired soldier data to the government affair system and the retired soldier management system.
Furthermore, the retired soldier big data analysis system further comprises a thematic analysis module, wherein the thematic analysis module comprises a plurality of rights and interests maintenance analysis units, an champion and pacifying analysis unit, a retired placement analysis unit, a military rest placement analysis unit, a employment and entrepreneur analysis unit and an education and training analysis unit;
the equity maintenance analysis unit is used for analyzing the acceptance condition of the letter visit and the visit of the retired soldier according to the retired soldier data, and/or analyzing the key difficult problem of the retired soldier, and/or analyzing the living state of the retired soldier;
the champion and pacifying analysis unit is used for analyzing the distribution condition of subsidy assistance according to the retired soldier data, and/or analyzing the distribution condition of the gore cards, and/or analyzing the implementation condition of a pacifying plan;
the retired army placement analysis unit is used for analyzing the going direction of a retired army and/or analyzing the implementation condition of a placement plan according to the retired army data;
the military rest arrangement analysis unit is used for analyzing the heading of military rest cadres in retired military personnel and/or analyzing the living state of the military rest cadres and/or analyzing the quality of military rest services according to the retired military personnel data;
the employment entrepreneurship analysis unit is used for analyzing the employment number, the employment direction and the entrepreneurship situation of the retired soldier according to the retired soldier data;
the education training analysis unit is used for analyzing the hot specialties, the education training effects and the conditions of retired soldier education training institutions according to the retired soldier data.
Further, the retired soldier big data analysis system further comprises a portal home page module; the portal home page module is used for providing the data resource module, the resource analysis module, the subject analysis module, the data service module and the subject analysis module.
Compared with the prior art, the invention has the beneficial effects that: the constitution framework of the system is set by constructing a retired soldier big data analysis system and adapting to the characteristics of retired soldier data, thereby realizing service datamation, data asset transformation and asset service transformation. On one hand, a data sharing channel can be effectively constructed, massive retired soldier data can be gathered, a data resource library can be constructed, and data can be searched in a key mode.
Drawings
Fig. 1 is a composition diagram of a retired military personnel big data analysis system according to an embodiment of the present invention.
Detailed Description
The drawings are only for purposes of illustration and are not to be construed as limiting the invention. For a better understanding of the following embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
As shown in fig. 1, the present embodiment provides a retired military personnel big data analysis system, which includes a data resource module 10, a resource analysis module 20, and a topic analysis module 30.
The data resource module 10 is configured to display a catalog of retired soldier data, and provide an entry for acquiring corresponding retired soldier data according to the catalog, where the catalog includes internal data, external data, and service data, the internal data is data acquired from a retired soldier management system, the external data is data acquired from a government system and an industry institution system, and the service data is data generated by a big data analysis system.
More specifically, the external data acquired from the administrative system includes security data, civil administration data, judicial data, human-society data, health data, market supervision data, natural resource data, and the like of retired soldiers; the external data acquired from the industrial institution system comprises medical data, education data, housing data, bank data, travel data and the like; the internal data comprises preferential treatment data, military reward and punishment data, arrangement data and the like; the service data comprises various result data obtained after the big data analysis system analyzes the retired soldier data.
The retired soldier management system is a system specially managing retired soldier affairs, such as retired soldier service systems in administrative districts at all levels. The government affair system is a government affair management system, such as a security system, a civil administration system, a judicial system and the like. The industry institution system is a management system of each institution of each industry in the society, and is a management system of some non-government affairs, such as a banking system of the financial industry, a traffic management system of the transportation industry and the like. The retired soldier data directory displayed by the data resource module 10 is divided into an internal data directory, an external data directory and a service data directory, and the internal data directory, the external data directory and the service data directory may also be subdivided directories.
The catalog displayed by the data resource module 10 provides overview and classification for massive retired soldier data, and forms a data resource library under different classifications, so that a user can more easily acquire required data through a retired soldier data entry corresponding to the catalog. The data resource module 10 improves the convenience of managing and using data by a user.
And the resource analysis module 20 is configured to perform statistical analysis on the retired soldier data in different dimensions to obtain a statistical analysis result, and display the statistical analysis result.
The statistical mode may include single field, double field and multiple field, which correspond to 1 field, 2 fields and 3 or more than 3 fields, respectively, and also correspond to one-dimensional, two-dimensional and three-dimensional or more than three-dimensional analysis dimension numbers, respectively.
In order to better mine the service value of the retired soldier data and excite the data vitality, the retired soldier data can be analyzed and displayed in a targeted manner according to different service themes, such as a petition theme, an employment and entrepreneurst theme, a preferential treatment theme and the like. Correspondingly, the topic analysis module 30 may include a visiting unit 31, a career creation unit 32, and a treatment unit 33.
And the credit visit unit 31 is configured to extract and analyze data of the retired soldier who is credited and visited from the retired soldier data, obtain statistical information of the retired soldier who is credited and visited, and display the statistical information.
The petition and visit is a way for the retired soldier to reflect the problems upwards, and the way can know the problems faced by the retired soldier in time and solve the problems in time. The petition visiting unit 31 extracts the data of the retired soldier who has been petitioned and visited to analyze, and displays statistical information about the petitioned and visited retired soldier according to the analysis, such as personnel category statistics, personnel quantity statistics, personnel region distribution and the like about the petitioned and visited retired soldier, so that a user can know the petitioned and visited conditions of the retired soldier on a macroscopic level.
And the employment startup unit 32 is used for extracting and analyzing the data of the retired soldier of the employment startup from the retired soldier data, obtaining the statistical information of the retired soldier of the employment startup, and displaying the statistical information.
The employment entrepreneurship is a key concern for the retired soldiers to transfer into the society, directly influences the life and income of the retired soldiers, and is an important factor for maintaining the stability of the society. The employment startup unit 32 extracts and analyzes the data of the retired soldier of the employment startup, and can quickly know the working arrangement condition, the personnel adaptation condition and the like of the retired soldier according to the statistical information of the retired soldier of the employment startup, such as the belonging industry statistics, the personnel number statistics, the personnel region distribution and the like of the retired soldier of the employment startup.
And the preferential treatment unit 33 is used for extracting and analyzing the data of the retired soldier who is the preferential object from the retired soldier data to obtain the statistical information of the preferential object and displaying the statistical information.
Retired soldiers and spouses, children and other career objects can obtain welfare treatment such as allowance. The pacifying treat unit 33 extracts the data of the pacifying object for analysis, and displays the statistical information about the pacifying object according to the analysis, so that the user can know the distribution situation of the body fluid patches, such as the region distribution, age distribution, fighting situation, disability situation and the like of the pacifying object.
The statistical information respectively displayed by the petition visiting unit 31, the employment entrepreneurship unit 32 and the preferential treatment unit 33 is helpful for the user to make decisions on the petition visiting strategy, the employment entrepreneurship strategy and the preferential treatment strategy respectively, so that the rationality, timeliness and pertinence of the decisions are improved.
The theme analysis module 30 may further include an integral display unit 34, where the integral display unit 34 may visually display the distribution of the retired soldiers, and may be configured to determine, according to the household registration information in the security data, a place name address and an administrative area to which the longitude and latitude information and the longitude and latitude information of each retired soldier belong, form dotting layers of different levels according to the place name address and the administrative area and the longitude and latitude information according to the administrative areas of different levels, form distribution maps of the retired soldiers of the administrative areas of different levels by combining the dotting layers of different levels with the map, and display the distribution maps.
The whole display unit 34 may be further configured to count the number of the retired soldiers in different levels in each administrative area according to the administrative area to which the longitude and latitude information of each retired soldier belongs, obtain a retired soldier number statistical list in the administrative areas in different levels, and synchronously display the number statistical list in the administrative areas in the same level as the retired soldier distribution chart when the distribution chart is displayed.
The whole display unit 34 displays the distribution situation graph and the quantity statistical list at the same time, so that the regional management capacity of the user on the retired soldier is further improved.
The topic analysis module 30 may also include a people-one-file unit 35. The one-person one-file unit 35 may be configured to extract personal data of one retired military person from the retired military person data, arrange the personal data into personal information, and display the personal information, where the personal information includes basic information, household registration information, social security information, family information, education background, military service information, visiting and visiting information, living information, visiting and visiting information, honor information, working information, tax payment information, preferential care information, disability information, poverty information, placement information, death information, and legal person information.
The one-person one-file unit 35 displays the basic information and the unique data corresponding to the identity category of each retired soldier in a unified manner, converts the data into information, and realizes value conversion of the data. Preferably, important information such as death information, disability information, poverty information, and the like can be highlighted.
Specifically, the one-person-one-file unit 35 may extract the data of the retired military person with the same identification number based on the identification number of the retired military person to obtain the personal data of the retired military person.
One person-one file unit 35 can also be used for analyzing the image of the retired soldier according to personal data to obtain an image tag of the retired soldier, the image tag is synchronously displayed when personal information is displayed, the type of the image tag comprises basic features, a credit case, a reward and punishment case, an education case, a working case and a placement case, and the basic features comprise a plurality of ages, sexes, native courts, marital states and political appearances.
For example, a portrait label for a retired military may be 38 years old, male, married, party members, military reptilities, college school calendar, annual income 50001-.
A soldier portrait of a retired soldier is constructed through the one-person one-file unit 35, intelligent current situation analysis and data insight of the retired soldier are facilitated, and accurate service of one-person one-decision is enabled.
The system for analyzing big data of retired military personnel provided by this embodiment may further include a data service module 40, where the data service module 40 may include one or more of a data governance unit 41, a data analysis unit 42, and a data sharing unit 43.
The data management unit 41 may be configured to sort, clean, and complement the retired soldier data, configure a data rule of the retired soldier data, search and issue problem data that does not meet the data rule from the retired soldier data, and generate a data quality report according to the problem data;
the data governance unit 41 may establish standard, quantitative data governance specifications to form a data rule configuration for retired soldier data. According to the configured data rule, problem data can be searched and issued in retired soldier data, a data quality report can be generated, and real-time treatment and monitoring can be carried out on the data quality in the big data analysis system.
The data analysis unit 42 may be configured to extract data of retired soldiers visited by letters from the retired soldier data and perform data collision analysis to determine a difficult problem of retired soldiers visited by letters, and/or extract data of retired soldiers entrusted with employment from the retired soldier data and perform data collision analysis to obtain a sentry matching analysis model and/or a special skill training model, and/or extract data of retired soldiers covered by a declaration from the retired soldier data and perform data collision analysis to obtain result data of the violation declaration, and push warning information according to the result data.
The data analysis unit 42 may perform special analysis on retired soldier data in many application scenarios, such as petition and visit, employment and entrepreneurship, and preferential treatment.
Under the application scene of the petition visit, when the field petition is given to the retired soldier, the petition service management department cannot comprehensively acquire the civil data of social insurance, medical insurance and the like of the retired soldier and the internal data of preferential treatment data, arrangement data and the like when checking information, the retired soldier needing petition visit firstly goes back and forth to multiple departments to take relevant certificates for petition visit, and meanwhile, the data of the retired soldier is easy to be incomplete, so that the phenomena of slow confirmation process and service congestion of the petition service management department are caused, secondary or multiple times of visit are also caused, the time cost and the traffic cost are higher, and even the phenomena of follow-up blocked visit and giving an alarm are caused. In addition, due to the fact that the petition system is split, the overlapping situation of multi-source appeal is serious, the same appeal source is different, the same petition case is accepted for multiple times, the same department conducts repeated handling, the workload loss of personnel is large, petition handling efficiency is seriously influenced, and the risk of overdue handling exists. The data analysis unit 42 can rapidly perform data unified scheduling query on the identities of the visitors and retired military personnel, perform unified classification analysis on the same type of data, perform collision analysis on personal information visually displayed in a one-person one-file mode by the one-person one-file unit 35, judge whether the visitors and retired military personnel meet related conditions, combine statistical information obtained by analysis of the visitors and access units 31, position problems once, perform service feedback solution on the positioned problems subsequently through telephone or on the spot, improve work efficiency, relieve the emotion of the visitors and reduce the risk of visiting.
Under the application scene of employment entrepreneurship, when a employment arrangement management department carries out the work recommendation and arrangement problem corresponding to retired soldiers in a coordinated mode, the retired soldiers can be recommended or matched and managed according to post information provided by enterprises and units, but the phenomena of insufficient working enthusiasm, poor working satisfaction degree, insufficient post adaptability, small rising space of subsequent posts and the like often occur due to the fact that the comprehensive personal information of the retired soldiers cannot be mastered quickly and accurately and corresponding post matching analysis is carried out, the phenomenon of employment or leaving is more again, the integral employment rate is low, the life of the retired soldiers cannot be guaranteed, the emotion is large, and certain risk factors exist. The data analysis unit 42 analyzes employment specials according to the retired soldier data, performs data collision fusion by combining personal information of the retired soldier with external data such as social recruitment, enterprise recruitment and the like, establishes a post matching analysis model, a specialized skill training model and the like, and directionally pushes retired soldiers meeting conditions for post recruitment planning and education planning. The data analysis unit 42 can also perform statistical comparison analysis on the plan execution rate and the subsequent job data, directionally adjust the strategy, and improve the employment service level.
Under the application scenario of preferential treatment, because the situation that the beneficiary loses the power of obtaining welfare treatment due to death or other abnormal reasons and continues to apply the benefits of other retired soldiers illegally occurs, the data analysis unit 42 can generate harm to the benefits of other retired soldiers, and can perform collision analysis according to the retired soldier list applying benefits, information of living conditions, houses, economic income, working conditions, social security, family addresses and the like of the retired soldiers, and retired soldier data of household registers, dead population, cremation funeral and interment, medical treatment and the like to obtain illegal apply benefits result data, and push an early warning signal to the user to remind the part of the retired soldiers of obtaining the qualification of welfare. The data analysis unit 42 may further perform trend analysis according to the relevant data of past subsidy distribution in the retired soldier data, so that the user may estimate the approved distribution plan again.
The data sharing unit 43 may be used to share retired military data to government systems and retired military management systems.
The data sharing unit 43 can establish an efficient information sharing and exchange mechanism, providing a horizontal data exchange.
In a preferred embodiment, the data service module 40 may further include a data security unit 44, where the data security unit 44 is configured to make a data inspection plan according to a preset security management specification, and perform security inspection on the retired soldier data according to the data inspection plan, including security inspection on the limits of entry and exit of the retired soldier data, and security inspection on the use of the retired soldier data. The data security unit 44 can prevent security risks and realize security control of the big data analysis system.
The big data analysis system for retired soldiers provided in this embodiment may further include a special analysis module 50 in cooperation with the theme analysis module 30, where the special analysis module 50 includes multiple equity maintenance analysis units 51, a champion career analysis unit 52, a retired placement analysis unit 53, a military rest placement analysis unit 54, a employment startup analysis unit 55, and an educational training analysis unit 56;
the equity maintenance analysis unit 51 is used for analyzing the acceptance condition of the letter visit and the visit of the retired soldier according to the retired soldier data, and/or analyzing the key difficult problems of the retired soldier, and/or analyzing the living state of the retired soldier;
a champion and caress analysis unit 52, configured to analyze issue conditions of subsidies and/or issue conditions of gore cards and/or analyze implementation conditions of champion plans according to retired soldier data;
a retired placement analysis unit 53, configured to analyze retired soldier heading and/or placement plan fulfillment based on retired soldier data;
a military rest arrangement analysis unit 54 for analyzing the going direction of military rest cadres in retired soldiers and/or analyzing the living state of the military rest cadres and/or analyzing the quality of military rest services according to retired soldier data;
the employment and entrepreneurship analysis unit 55 is used for analyzing the employment number, employment direction and entrepreneurship of the retired soldiers according to the retired soldier data;
and the education training analysis unit 56 is used for analyzing the hot specialties, the education training effects and the conditions of the education training institutions of the retired soldiers according to the retired soldier data.
The topic analysis module 30 and the special topic analysis module 50 are matched with each other, and the analysis results of the topic analysis module and the special topic analysis module can be combined with each other, so that efficient and accurate decision making can be performed on all affairs of retired soldiers.
The results analyzed by the data governance unit 41 and the data analysis unit 42 in the theme analysis module 30, the special topic analysis module 50 and the data service module 40 can all select the required result through the customized interface and display the result on the same interface.
The system for analyzing big data of retired military personnel provided by this embodiment may further include a portal home page module 60, where the portal home page module 60 is configured to provide entries to the data resource module 10, the resource analysis module 20, the topic analysis module 30, the data service module 40, and the topic analysis module 50.
The user can conveniently find the entrance of each module through the portal home page module 60.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the technical solutions of the present invention, and are not intended to limit the specific embodiments of the present invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention claims should be included in the protection scope of the present invention claims.
Claims (10)
1. A big data analysis system for retired soldiers is characterized by comprising a data resource module, a resource analysis module and a theme analysis module;
the data resource module is used for displaying a catalogue of retired soldier data and providing an entrance for acquiring the retired soldier data according to the catalogue, wherein the catalogue comprises internal data, external data and service data, the internal data is data acquired from a retired soldier management system, the external data is data acquired from a service system and an industry mechanism system, and the service data is data generated by the big data analysis system;
the resource analysis module is used for carrying out statistical analysis of different dimensions on the retired soldier data to obtain a statistical analysis result and displaying the statistical analysis result;
the theme analysis module comprises a petition visiting unit, an employment entrepreneurship unit and a pacifying and treating unit;
the petition visiting unit is used for extracting and analyzing the data of the refuge visitors from the data of the retired soldiers to obtain the statistical information of the refuge visitors to be visited and displaying the statistical information;
the employment startup unit is used for extracting and analyzing the data of the retired soldiers of the employment startup from the retired soldier data to obtain the statistical information of the retired soldiers of the employment startup and displaying the statistical information;
and the preferential treatment unit is used for extracting and analyzing the data of the retired soldier who is a preferential object from the retired soldier data to obtain the statistical information of the preferential object and displaying the statistical information.
2. The big data analysis system of retired soldier according to claim 1, wherein the external data obtained from the government system comprises retired soldier security data, civil administration data, judicial data, human-social data, health data, market regulatory data, natural resource data; the external data acquired from the industry institution system includes medical data, educational data, housing data, bank data, and travel data.
3. The decommissioned military personnel big data analysis system according to claim 2, wherein the theme analysis module further comprises an integral display unit;
the integral display unit is used for determining longitude and latitude information of each retired soldier and a place name address and an administrative area to which the longitude and latitude information belongs according to the household registration information in the safety data, forming dotting layers of different levels according to the longitude and latitude information and administrative areas of different levels according to the place name address and the administrative area, combining the dotting layers of different levels with a map to form a retired soldier distribution situation map of the administrative areas of different levels, and displaying the distribution situation map.
4. The big data analysis system for retired soldiers according to claim 3, wherein the integral display unit is further configured to count the number of retired soldiers in different levels in each administrative area according to the administrative area to which the longitude and latitude information of each retired soldier belongs, obtain a statistical list of the number of retired soldiers in different levels of administrative areas, and synchronously display the statistical list of the number of administrative areas in the same level as the distribution map of the retired soldiers when displaying the distribution map.
5. The decommissioned military personnel big data analysis system of claim 2, wherein the topic analysis module further comprises a person-to-document unit;
the one-person one-file unit is used for extracting personal data of one retired military person from the retired military person data, arranging the personal data into personal information and displaying the personal information, wherein the personal information comprises basic information, household registration information, social security information, family information, education background, military service information, information of visiting and visiting, living information, visiting and visiting information, honor information, working information, tax payment information, preferential treatment information, disability information, poverty information, arrangement information, death information and legal person information.
6. The decommissioned soldier big data analysis system according to claim 5, wherein the one-person one-file unit is further configured to perform decommissioned soldier portrait analysis according to the personal data to obtain portrait tags of the decommissioned soldiers, and the portrait tags are synchronously displayed when the personal information is displayed, the portrait tags are of types including basic features, credibility, punishment, education, work and arrangement, and the basic features include multiple ages, sexes, native fates, marital states and political appearances.
7. The big data analysis system of retired soldier according to claim 1, wherein the resource analysis module is specifically configured to determine the number of selectable fields according to the selected statistical manner, determine analysis dimensions according to the selected fields, perform statistical analysis of different dimensions on retired soldier data according to the determined analysis dimensions, obtain statistical analysis results, and display the statistical analysis results, wherein the fields include a plurality of categories of personnel, visiting and months, regional distribution, political aspects, household nationality categories, age distribution, income per year, service age, retirement manner, social insurance, enjoying enjoyment, and culture degree.
8. The retired military personnel big data analysis system of claim 1, further comprising a data service module, wherein the data service module comprises one or more of a data governance unit, a data analysis unit, and a data sharing unit;
the data management unit is used for carrying out classified carding, cleaning and completion on the retired soldier data, configuring a data rule of the retired soldier data, searching and issuing problem data which do not accord with the data rule from the retired soldier data, and generating a data quality report according to the problem data;
the data analysis unit is used for extracting the data of the retired soldier who visits and visits from the retired soldier data and performing data collision analysis to determine the difficult problem of the retired soldier who visits and visits, and/or is used for extracting the data of the retired soldier who enters employment and entrepreneurship from the retired soldier data and performing data collision analysis to obtain a sentry matching analysis model and/or a special skill training model, and/or is used for extracting the data of the retired soldier who applies to the application allowance from the retired soldier data and performing data collision analysis to obtain the result data of the illegal application allowance, and early warning information is pushed according to the result data;
the data sharing unit is used for sharing the retired soldier data to the government affair system and the retired soldier management system.
9. The decommissioned soldier big data analysis system according to claim 8, further comprising a thematic analysis module, wherein the thematic analysis module comprises a plurality of equity maintenance analysis units, champion stroking analysis units, decommissioned placement analysis units, champion placement analysis units, employment startup analysis units, educational training analysis units;
the equity maintenance analysis unit is used for analyzing the acceptance condition of the letter visit and the visit of the retired soldier according to the retired soldier data, and/or analyzing the key difficult problem of the retired soldier, and/or analyzing the living state of the retired soldier;
the champion and pacifying analysis unit is used for analyzing the distribution condition of subsidy assistance according to the retired soldier data, and/or analyzing the distribution condition of the gore cards, and/or analyzing the implementation condition of a pacifying plan;
the retired army placement analysis unit is used for analyzing the going direction of a retired army and/or analyzing the implementation condition of a placement plan according to the retired army data;
the military rest arrangement analysis unit is used for analyzing the heading of military rest cadres in retired military personnel and/or analyzing the living state of the military rest cadres and/or analyzing the quality of military rest services according to the retired military personnel data;
the employment entrepreneurship analysis unit is used for analyzing the employment number, the employment direction and the entrepreneurship situation of the retired soldier according to the retired soldier data;
the education training analysis unit is used for analyzing the hot spot specialties, the education training effects and the conditions of retired soldier education training institutions of retired soldiers according to the retired soldier data.
10. The decommissioned military personnel big data analysis system of claim 9, further comprising a portal homepage module;
the portal home page module is used for providing the data resource module, the resource analysis module, the subject analysis module, the data service module and the subject analysis module.
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| CN202111013289.7A CN113641660A (en) | 2021-08-31 | 2021-08-31 | Big data analysis system for retired soldier |
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| CN202111013289.7A CN113641660A (en) | 2021-08-31 | 2021-08-31 | Big data analysis system for retired soldier |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110781236A (en) * | 2019-10-29 | 2020-02-11 | 山西云时代技术有限公司 | Method for constructing government affair big data management system |
| WO2020114138A1 (en) * | 2018-12-06 | 2020-06-11 | 西安光启未来技术研究院 | Information associated analysis method and apparatus, and storage medium and electronic device |
| CN112465317A (en) * | 2020-11-16 | 2021-03-09 | 广东电网有限责任公司 | Cadre portrait information analysis system based on big data |
| CN112507084A (en) * | 2020-12-16 | 2021-03-16 | 江苏尊荣信息科技有限公司 | Information resource integration and sharing platform for retired soldiers |
-
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020114138A1 (en) * | 2018-12-06 | 2020-06-11 | 西安光启未来技术研究院 | Information associated analysis method and apparatus, and storage medium and electronic device |
| CN110781236A (en) * | 2019-10-29 | 2020-02-11 | 山西云时代技术有限公司 | Method for constructing government affair big data management system |
| CN112465317A (en) * | 2020-11-16 | 2021-03-09 | 广东电网有限责任公司 | Cadre portrait information analysis system based on big data |
| CN112507084A (en) * | 2020-12-16 | 2021-03-16 | 江苏尊荣信息科技有限公司 | Information resource integration and sharing platform for retired soldiers |
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