CN115809308A - Method, device and electronic equipment for realizing automatic classification and collection of real population data - Google Patents
Method, device and electronic equipment for realizing automatic classification and collection of real population data Download PDFInfo
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Abstract
The application discloses a method, a device and electronic equipment for realizing automatic classification and collection of real population data, wherein the method comprises the following steps: s1, collecting various social data, public security business data, government, enterprise and institution unit data and the like by using a big data platform; s2, analyzing to form a standard address library on the basis of address data of the residential building and residential property data; s3, establishing an incidence relation between the established house owner data and the standard address library, and forming a personnel information base library; and S4, performing correlation analysis on the personnel information base, the civil marriage data, the public security household data and the national population data of the public security department to obtain a detailed personnel information base and a personnel house correlation base, and realizing automatic classification and acquisition of the actual population data. According to the method and the system, through a big data technology, the workload of sending out the policemen is greatly reduced, and the accuracy and timeliness of relevant real population data are ensured, so that the construction and management of the current social security prevention and control system are facilitated.
Description
Technical Field
The present application relates to the field of information processing technologies, and in particular, to a method, an apparatus, and an electronic device for implementing automatic classification and collection of real population data.
Background
The management of real population becomes the most important problem for the construction of the public security prevention and control system of the current society. The management mode of the real population in the district with the party and the community as the unit has become the main mode of the real population management of the current public security organization. With the development of economy in China, floating population is more and more, the mode of originally relying on the management of household population cannot meet the more and more complex form change of the modern society, and the current actual living and activity conditions of real population cannot be really mastered. The real population management system is developed for better managing and mastering the inflow, outflow, activity and other situations of the real population.
The current management mode of real population is mainly carried out in a mode that police, police assistants, community managers and the like are dispatched and are visited and investigated manually and regularly, and basic information, family member information, contact information and the like of people registered by a word paper account or a mobile police APP register are used for each home. There are a number of problems with this approach: 1. the population base number of the jurisdictions is large, and the verification workload is heavy; 2. the problem that people are not at home and need to repeatedly check at home during the home check is often encountered during the home check, and police resources are seriously wasted; 3. real population flowing into and out of the jurisdiction cannot find and master in time, and real population data is not updated in time; 4. police officers are insufficient in strength, limited in quantity and incapable of achieving face to face, so that problems of missed collection, untimely updating and the like exist in real population.
Disclosure of Invention
In view of the above technical problems, the present application provides a method for automatically classifying and collecting real population data.
The technical scheme adopted by the application is as follows:
a method for realizing automatic classification and collection of real population data comprises the following steps:
s1, collecting various social data, public security business data, government department data and enterprise and public institution unit data by using a big data platform, wherein the social data, the public security household data, the civil marriage data, portrait data and front-end perception data are included;
s2, analyzing the address data of the house building production data by using an NLP natural language processing technology, and continuously updating and enriching the address data to form a standard address library according to the standard address building specification of the ministry of public security;
s3, establishing an incidence relation between the data of the house owner and a standard address base, and forming a personnel information base, wherein the personnel information base comprises personnel basic information data, and the personnel basic information data comprises an identity card number, a name, a contact telephone and household registration information;
and S4, performing association analysis on the personnel information base, the civil marriage data, the public security household data and the national population data of the public security department, supplementing and perfecting personnel basic information data items in the personnel information base, establishing an association relation between population and a house, obtaining a detailed personnel information base and a people and house association base, and realizing automatic classification and acquisition of real population data.
Further, the method also comprises the following steps:
and S5, performing correlation analysis collision on data in the standard address base and the personnel information base by continuously accessing various local social data and government data, and continuously improving the data accuracy of the standard address base and the personnel information base.
Further, the step S4 specifically includes the steps of:
and S41, performing correlation analysis on the personnel information base and civil marriage data by using a big data flow type computing technology, finding spouse data corresponding to the homeowner through homeowner data, incorporating the homeowner spouse data into the personnel information base, and establishing a correlation relationship between a standard address associated with the homeowner and the spouse data.
Further, the step S4 specifically includes the steps of:
and S42, performing correlation analysis on the personnel information base and the public security household registration data by using a big data flow type computing technology, finding corresponding personnel information of the same household through a household mouth for the population data corresponding to the personnel information base, bringing the personnel information of the same household into the personnel information base, associating a standard address, and further perfecting the personnel information base.
Further, the step S4 specifically includes the steps of:
s43, by utilizing a big data flow type computing technology, the basic data of household registers and population and the national population data of the Ministry of public Security are facilitated, basic information data items of personnel in a personnel information basic library are automatically supplemented and perfected, meanwhile, the incidence relation of population houses is established, the detailed personnel information basic library and a personnel house incidence library are obtained, and automatic classification and collection of real population data are realized.
Further, the step S5 specifically includes the steps of:
s501, performing collision comparison by using face snapshot data of an intelligent community and combining portrait data with a base and an identity card number of a personnel information base to obtain corresponding personnel basic information data;
s502, carrying out correlation analysis by using personnel information and house owner data of the same cell, and if the snap-shot personnel exist in a personnel information base, confirming the actual residential building and house number of the personnel;
s503, if the person in the personnel information basic library is never captured by the face of the cell, the fact that the person possibly does not live in the cell is indicated, and the identity corresponding to the person who does not live in the address is marked in the personnel information basic library.
Further, the step S5 specifically includes the steps of:
s511, accessing local public security, government and other social data, including basic information data of personnel filled in the local government, public security and social security business handling, and basic information data of personnel filled in the logistics consignment business;
s512, carrying out collision comparison on the accessed local public security, government and other social data and the address and the identity card number of the personnel information base to obtain corresponding personnel basic information data;
s513, if the acquired basic personnel information data is not found in the personnel information base, bringing the acquired basic personnel information data into the personnel information base, filling and perfecting the personnel information base and the standard address base, and establishing an association relationship between personnel and addresses;
and S514, if the acquired basic information data of the personnel is stored in the personnel information base and the acquired basic information data of the personnel is different from the corresponding basic information data of the personnel in the personnel information base, updating and perfecting the corresponding basic information data of the personnel in the personnel information base, the standard address base and the incidence relation of the two.
This application another aspect still provides a device that realizes automatic classification of real population data and gather, includes:
the big data collecting module is used for collecting various social data, public security business data, government department data and enterprise and public institution unit data by using a big data platform, wherein the social data, the public security business data, the civil marriage data, the portrait data and the front-end perception data are collected by using the big data platform;
the standard address base construction module is used for analyzing the address data of the housing building production data by using the NLP natural language processing technology, and continuously updating and filling the address data to form a standard address base according to the standard address construction specification of the ministry of public security;
the system comprises a personnel information base building module, a standard address base building module and a personnel information base building module, wherein the personnel information base building module is used for building an incidence relation between house owner data and the standard address base and forming a personnel information base, the personnel information base comprises personnel basic information data, and the personnel basic information data comprises identity card numbers, names, contact phones and household registration information;
and the association analysis module is used for performing association analysis on the personnel information base, civil marriage data, public security household data and national population data of the public security department, supplementing and perfecting personnel basic information data items in the personnel information base, establishing association relation between population and houses, obtaining a detailed personnel information base and a people and house association base, and realizing automatic classification and acquisition of real population data.
Further, the method also comprises the following steps:
and the data checking module is used for performing correlation analysis collision on the data in the standard address base and the personnel information base by continuously accessing various local social data and government data, and continuously improving the data accuracy of the standard address base and the personnel information base.
The present application also provides an electronic device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method for automatically classifying and collecting real population data.
The application also provides a storage medium, which comprises a stored program, and when the program runs, the device on which the storage medium is located is controlled to execute the steps of the method for realizing automatic classification and collection of real population data.
Compared with the prior art, the method has the following beneficial effects:
the application provides a method, a device and electronic equipment for realizing automatic classification and collection of real population data, wherein the method comprises the following steps: s1, collecting various social data, public security business data, government department data and enterprise and public institution unit data by using a big data platform, wherein the social data, the public security household data, the civil marriage data, portrait data and front-end perception data are included; s2, analyzing the address data of the house building production data by using an NLP natural language processing technology, and continuously updating and enriching the address data to form a standard address library according to the standard address building specification of the ministry of public security; s3, establishing an incidence relation between the data of the house owner and a standard address base, and forming a personnel information base, wherein the personnel information base comprises personnel basic information data, and the personnel basic information data comprises an identity card number, a name, a contact telephone and household registration information; and S4, performing correlation analysis on the personnel information base, civil marriage data, public security household data and national population data of the public security department, supplementing and perfecting personnel basic information data items in the personnel information base, establishing an incidence relation between population and a house, obtaining a detailed personnel information base and a human-house incidence base, and realizing automatic classification and collection of actual population data.
In order to reduce the workload of sending the home check data of policemen, fully release police resources and enhance the timeliness of updating real population data, the present big data technology is utilized to solve the management problem of the current real population, the real population association relation based on standard addresses is established by integrating social data, public security service data, government data, enterprise and public institution data, front end perception and other data and performing comprehensive analysis, the inflow and outflow conditions of the real population are automatically discovered, and the basic information of the real population is automatically collected and updated. The police dispatch does not need to check every family and visit, and does not need to pay attention to inflow and outflow conditions of real population in the district; according to the method, the big data is established, the actual population information is actively discovered and updated, the actual population information is discovered by the people through the prior arrangement of the polices, and the actual population information is discovered by the big data; the data is updated and maintained by policemen in a real population system, and is automatically updated and maintained after being analyzed by big data; the data which are abnormal are pushed to the corresponding police station policemen to be verified, so that the police station policemen do not need to go home to verify, manual data maintenance is not needed, the police station policemen only need to master the reminding information automatically pushed by the system, the workload of the police station policemen is greatly reduced, the accuracy and the timeliness of relevant actual population data are guaranteed, and the construction and the management of the current social security prevention and control system are facilitated.
In addition to the above-described objects, features and advantages, there are other objects, features and advantages of the present application. The present application will now be described in further detail with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
fig. 1 is a flow chart of a method for implementing automatic classification and collection of real population data according to a preferred embodiment of the present application.
Fig. 2 is a flow chart of a method for implementing automatic classification and collection of real population data according to another preferred embodiment of the present application.
Fig. 3 is a flow chart illustrating the sub-steps of step S4 according to the preferred embodiment of the present application.
Fig. 4 is a flow chart illustrating the sub-steps of step S4 according to another preferred embodiment of the present application.
Fig. 5 is a flow chart illustrating the sub-steps of step S4 according to another preferred embodiment of the present application.
Fig. 6 is a flow chart illustrating the sub-steps of step S5 according to the preferred embodiment of the present application.
Fig. 7 is a flow chart illustrating the sub-steps of step S5 according to another preferred embodiment of the present application.
Fig. 8 is a module diagram of an apparatus for implementing automatic classification and collection of real population data according to the preferred embodiment of the present application.
Fig. 9 is a schematic block diagram of an apparatus for implementing automatic classification and collection of real population data according to another preferred embodiment of the present application.
Fig. 10 is a schematic block diagram of an electronic device entity of the preferred embodiment of the present application.
Fig. 11 is an internal structural view of a computer device of the preferred embodiment of the present application.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Referring to fig. 1, a preferred embodiment of the present invention provides a method for automatically classifying and collecting real population data, comprising the steps of:
s1, collecting various social data, public security business data, government department data and enterprise and public institution data by using a big data platform, wherein the social data, the public security household data, the civil marriage data, portrait data and front-end sensing data are included;
s2, analyzing the address data of the residential building product data by using an NLP natural language processing technology, and continuously updating and enriching the address data to form a standard address library according to the standard address construction specification of the public security ministry;
s3, establishing an incidence relation between the data of the house owner and a standard address base, and forming a personnel information base, wherein the personnel information base comprises personnel basic information data, and the personnel basic information data comprises an identity card number, a name, a contact telephone and household registration information;
and S4, performing correlation analysis on the personnel information base, civil marriage data, public security household data and national population data of the public security department, supplementing and perfecting personnel basic information data items in the personnel information base, establishing an incidence relation between population and a house, obtaining a detailed personnel information base and a human-house incidence base, and realizing automatic classification and collection of actual population data.
In order to reduce the workload of sending the home check data of policemen, fully release police resources and enhance the timeliness of updating real population data, the present big data technology is utilized to solve the management problem of the current real population, the real population association relation based on standard addresses is established by integrating social data, public security service data, government data, enterprise and public institution data, front end perception and other data and performing comprehensive analysis, the inflow and outflow conditions of the real population are automatically discovered, and the basic information of the real population is automatically collected and updated. The police dispatch does not need to check every family and visit, and does not need to pay attention to inflow and outflow conditions of real population in the district; according to the method, the big data is established, the actual population information is actively discovered and updated, the actual population information is discovered by the people through the prior arrangement of the polices, and the actual population information is discovered by the big data; the original method is that the policeman updates and maintains data in a real population system, and the data are automatically updated and maintained after being analyzed by big data; the data with abnormity is pushed to the corresponding police dispatching place policemen for verification, so that the police dispatching place policemen do not need to check every family, and also do not need to manually maintain data, the police dispatching place policemen only need to master the reminding information automatically pushed by the system, the workload of the police dispatching place policemen is greatly reduced, the accuracy and the timeliness of relevant real population data are ensured, and the construction and the management of the current social security prevention and control system are facilitated.
This application mainly maintains real population data around realizing automatic collection, the problem that reduces community policeman's work load is developed, carry out the analysis to data through big data technology, realize the update and the maintenance of data automatically, community policeman's work load has been reduced, the traditional mode that has the policeman of sending out and carry out artifical collection check is seen one by one to the house, real population automatic information acquisition automatic discovery has been realized, automatic acquisition, the automatic maintenance is updated.
In another preferred embodiment of the present application, as shown in fig. 2, the method for automatically classifying and collecting real population data further comprises the steps of:
and S5, performing correlation analysis collision on the data in the standard address base and the personnel information base by continuously accessing various local social data and government data, and continuously improving the data accuracy of the standard address base and the personnel information base.
A basic personnel information base library is basically formed through the steps S1 to S4, but the association between the population data and the address at this time is not necessarily completely accurate, for example: the same family population does not necessarily live in the same address with the homeowner; the spouses do not necessarily all live under the same address; nor do homeowners necessarily live in purchased houses. Therefore, the data accuracy needs to be further checked through other data, and in the embodiment, the data in the standard address base and the data in the personnel information base are further subjected to correlation analysis and collision through continuous access to various local social data and government data, so that the data accuracy of the standard address base and the personnel information base is continuously improved, the accurate correlation between the population data and the address is ensured as much as possible, and the existing errors are eliminated.
As shown in fig. 3, in another preferred embodiment of the present application, the step S4 specifically includes the steps of:
and S41, performing association analysis on the personnel information base and civil marriage data by using a big data stream type calculation technology, finding spouse data corresponding to a house owner through house owner data, bringing the house owner spouse data into the personnel information base, and establishing an association relation between a standard address associated with the house owner and the spouse data so as to associate the standard address associated with the house owner in the personnel information base with the spouse data.
As shown in fig. 4, in another preferred embodiment of the present application, the step S4 further includes the steps of:
and S42, performing association analysis on the personnel information base and the public security household registration data by using a big data flow type computing technology, finding corresponding household personnel information through a household mouth for the population data corresponding to the personnel information base, bringing the household personnel information into the personnel information base, associating a standard address, and further perfecting the personnel information base.
As shown in fig. 5, in another preferred embodiment of the present application, the step S4 further includes the steps of:
s43, by utilizing a big data flow type computing technology, the basic data of household registers and population and the national population data of the Ministry of public Security are facilitated, basic information data items of personnel in a personnel information basic library are automatically supplemented and perfected, meanwhile, the incidence relation of population houses is established, the detailed personnel information basic library and a personnel house incidence library are obtained, and automatic classification and collection of real population data are realized.
In this embodiment, on the basis of the steps S42 to S42, the authority data such as the household registration population basic data and the national population data of the police department are further used to automatically supplement and improve the personnel basic information data items in the personnel information basic library, and meanwhile, the association relationship of the population and the house is established, so as to obtain the detailed personnel information basic library and the personnel and house association library, thereby further improving the accuracy of the personnel information basic library.
As shown in fig. 6, in another preferred embodiment of the present application, the step S5 specifically includes the steps of:
s501, performing collision comparison by using face snapshot data of an intelligent community and combining portrait data with a base and an identity card number of a personnel information base to obtain corresponding personnel basic information data;
s502, carrying out correlation analysis by utilizing personnel information and house owner data of the same cell, and if the snap-shot personnel exist in a personnel information basic library, confirming the actual residential buildings and house numbers of the personnel;
s503, if the person in the personnel information basic library is never captured by the face of the cell, the fact that the person possibly does not live in the cell is indicated, and the identity corresponding to the person who does not live in the address is marked in the personnel information basic library.
In order to further verify the accuracy of data, more data are needed for auxiliary analysis, and therefore, the data can be processed according to the data condition of self access of public security big data, the embodiment utilizes the face snapshot data of an intelligent community, combines with the human image data and the base and identity card number of the personnel information base to perform collision comparison to verify the accuracy of the corresponding relationship between the personnel in the personnel information base and the actual residential building and house number, if the snapshot personnel exist in the personnel information base, the actual residential building and house number of the person can be verified, if the person in the personnel information base is never snapped by the face of the community, the person is possibly not resident in the community, meanwhile, the person is marked with the identification which the person should not live under the address in the personnel information base, and the accuracy of the association relationship between the personnel and the residential address is further calibrated and verified.
As shown in fig. 7, in another preferred embodiment of the present application, the step S5 specifically includes the steps of:
s511, accessing local public security, government and other social data, including basic information data of personnel filled in the process of handling the local government, the public security and social security business and basic information data of personnel filled in the logistics consignment business;
s512, carrying out collision comparison on the accessed local public security, government and other social data and the address and the identity card number of the personnel information base to obtain corresponding personnel basic information data;
s513, if the acquired basic personnel information data is not found in the personnel information base, bringing the acquired basic personnel information data into the personnel information base, filling and perfecting the personnel information base and the standard address base, and establishing an association relationship between personnel and addresses;
and S514, if the acquired basic information data of the personnel is stored in the personnel information base and the acquired basic information data of the personnel is different from the corresponding basic information data of the personnel in the personnel information base, updating and perfecting the corresponding basic information data of the personnel in the personnel information base, the standard address base and the incidence relation of the two.
In this embodiment, if there is no face data of the cell, local public security, government and other social data can be accessed for analysis and comprehensive analysis. Such as: the filled-in address data is analyzed and processed through NLP natural language identification, and the actual address information of the people can be judged. If the accessed data is not found in the personnel information basic library after being analyzed, the accessed data needs to be brought into the personnel information basic library, and the personnel basic library is continuously improved. By continuously accessing various social data and government data and carrying out correlation analysis collision on the data and the personnel information base, the data accuracy of the personnel information base and the standard address base can be continuously improved. Such as: the information filled in by enterprise personnel data, social security data, public security certificate business handling data, nucleic acid examination data, hospital hospitalization data and the like can be used for continuously improving the association relationship among the personnel information base, the standard address base and the two bases, and finally the data accuracy of the association relationship among the personnel information base, the standard address base and the two bases is gradually close to 100%.
As shown in fig. 8, another preferred embodiment of the present invention provides an apparatus for automatically classifying and collecting real population data, including:
the big data collecting module is used for collecting various social data, public security business data, government department data and enterprise and public institution unit data by using a big data platform, wherein the various social data, the public security household data, the civil marriage data, the portrait data and the front-end sensing data are included;
the standard address base construction module is used for analyzing the address data of the residential building product data by utilizing the NLP natural language processing technology, and continuously updating and enriching the address data to form a standard address base according to the standard address construction standard of the ministry of public security;
the system comprises a personnel information base building module, a standard address base building module and a personnel information base building module, wherein the personnel information base building module is used for building an incidence relation between house owner data and the standard address base and forming a personnel information base, the personnel information base comprises personnel basic information data, and the personnel basic information data comprises identity card numbers, names, contact phones and household registration information;
and the association analysis module is used for performing association analysis on the personnel information base, civil marital data, public security household data and national population data of the public security department, supplementing and perfecting personnel basic information data items in the personnel information base, establishing an association relation between population and a house, obtaining a detailed personnel information base and a human-house association base, and realizing automatic classification and collection of real population data.
In another preferred embodiment of the present application, as shown in fig. 9, the apparatus for automatically classifying and collecting real population data further includes:
and the data checking module is used for performing correlation analysis collision on the data in the standard address base and the personnel information base by continuously accessing various local social data and government data, and continuously improving the data accuracy of the standard address base and the personnel information base.
As shown in fig. 10, the preferred embodiment of the present application further provides an electronic device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the method for implementing automatic categorization and collection of real population data in the foregoing embodiments are implemented.
As shown in fig. 11, the preferred embodiment of the present application also provides a computer device, which may be a terminal or a biopsy server, and the internal structure thereof may be as shown in fig. 11. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with other external computer devices through network connection. The computer program is executed by a processor to realize the steps of the method for realizing the automatic classification and collection of the real population data.
Those skilled in the art will appreciate that the architecture shown in fig. 11 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The preferred embodiment of the present application further provides a storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus where the storage medium is located is controlled to execute the steps of the method for automatically classifying and collecting real population data in the foregoing embodiment.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than here.
If the functions of the method of the present embodiment are implemented in the form of software functional units and sold or used as independent products, the functions may be stored in one or more storage media readable by a computing device. Based on such understanding, part of the contribution to the prior art of the embodiments of the present application or part of the technical solution may be embodied in the form of a software product stored in a storage medium and including several instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the present application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A method for realizing automatic classification and collection of real population data is characterized by comprising the following steps:
s1, collecting various social data, public security business data, government department data and enterprise and public institution data by using a big data platform, wherein the social data, the public security household data, the civil marriage data, portrait data and front-end sensing data are included;
s2, analyzing the address data of the house building production data by using an NLP natural language processing technology, and continuously updating and enriching the address data to form a standard address library according to the standard address building specification of the ministry of public security;
s3, establishing an incidence relation between the home owner data and a standard address base, and forming a personnel information base, wherein the personnel information base comprises personnel basic information data, and the personnel basic information data comprises an identity card number, a name, a contact telephone and household registration information;
and S4, performing correlation analysis on the personnel information base, civil marriage data, public security household data and national population data of the public security department, supplementing and perfecting personnel basic information data items in the personnel information base, establishing an incidence relation between population and a house, obtaining a detailed personnel information base and a human-house incidence base, and realizing automatic classification and collection of actual population data.
2. The method for automatically classifying and collecting real population data as claimed in claim 1, further comprising the steps of:
and S5, performing correlation analysis collision on the data in the standard address base and the personnel information base by continuously accessing various local social data and government data, and continuously improving the data accuracy of the standard address base and the personnel information base.
3. The method for automatically classifying and collecting real population data according to claim 1, wherein the step S4 specifically comprises the steps of:
and S41, performing association analysis on the personnel information base and civil marriage data by using a big data stream type calculation technology, finding spouse data corresponding to the homeowner according to the data of the homeowner, bringing the spouse data of the homeowner into the personnel information base, and establishing an association relation between a standard address associated with the homeowner and the spouse data.
4. The method for automatically classifying and collecting real population data according to claim 3, wherein the step S4 further comprises the steps of:
and S42, performing correlation analysis on the personnel information base and the public security household registration data by using a big data flow type computing technology, finding corresponding personnel information of the same household through a household mouth for the population data corresponding to the personnel information base, bringing the personnel information of the same household into the personnel information base, associating a standard address, and further perfecting the personnel information base.
5. The method for automatically classifying and collecting demographic data according to claim 4, wherein the step S4 further comprises the steps of:
s43, by utilizing a big data flow type computing technology, the basic data of household registers and population and the national population data of the Ministry of public Security are facilitated, basic information data items of personnel in a personnel information basic library are automatically supplemented and perfected, meanwhile, the incidence relation of population houses is established, the detailed personnel information basic library and a personnel house incidence library are obtained, and automatic classification and collection of real population data are realized.
6. The method for automatically classifying and collecting real population data according to claim 2, wherein the step S5 specifically comprises the steps of:
s501, performing collision comparison by using face snapshot data of an intelligent community and combining portrait data with a base and an identity card number of a personnel information base to obtain corresponding personnel basic information data;
s502, carrying out correlation analysis by using personnel information and house owner data of the same cell, and if the snap-shot personnel exist in a personnel information base, confirming the actual residential building and house number of the personnel;
s503, if the person in the personnel information basic library is never captured by the face of the cell, the fact that the person possibly does not live in the cell is indicated, and the identity corresponding to the person who does not live in the address is marked in the personnel information basic library.
7. The method for automatically classifying and collecting real population data according to claim 6, wherein the step S5 specifically comprises the steps of:
s511, accessing local public security, government and other social data, including basic information data of personnel filled in the local government, public security and social security business handling, and basic information data of personnel filled in the logistics consignment business;
s512, carrying out collision comparison on the accessed local public security, government and other social data and the address and the identity card number of the personnel information base to obtain corresponding personnel basic information data;
s513, if the acquired basic personnel information data are not found in the basic personnel information base, bringing the acquired basic personnel information data into the basic personnel information base, filling and completing the basic personnel information base and the standard address base, and establishing an association relationship between personnel and an address;
and S514, if the acquired basic information data of the personnel already exist in the personnel information base and the acquired basic information data of the personnel are different from the corresponding basic information data of the personnel in the personnel information base, updating and perfecting the corresponding basic information data of the personnel in the personnel information base, the standard address base and the incidence relation of the basic information data of the personnel and the standard address base.
8. An apparatus for implementing automatic classification and collection of real population data, comprising:
the big data collecting module is used for collecting various social data, public security business data, government department data and enterprise and public institution unit data by using a big data platform, wherein the social data, the public security business data, the civil marriage data, the portrait data and the front-end perception data are collected by using the big data platform;
the standard address base construction module is used for analyzing the address data of the residential building product data by utilizing the NLP natural language processing technology, and continuously updating and enriching the address data to form a standard address base according to the standard address construction standard of the ministry of public security;
the system comprises a personnel information base building module, a standard address base building module and a personnel information base building module, wherein the personnel information base building module is used for building an incidence relation between house owner data and the standard address base and forming a personnel information base, the personnel information base comprises personnel basic information data, and the personnel basic information data comprises identity card numbers, names, contact phones and household registration information;
and the association analysis module is used for performing association analysis on the personnel information base, civil marriage data, public security household data and national population data of the public security department, supplementing and perfecting personnel basic information data items in the personnel information base, establishing association relation between population and houses, obtaining a detailed personnel information base and a people and house association base, and realizing automatic classification and acquisition of real population data.
9. The apparatus for automatically categorizing and collecting demographic data as set forth in claim 8, further comprising:
and the data checking module is used for performing correlation analysis collision on the data in the standard address base and the personnel information base by continuously accessing various local social data and government data, and continuously improving the data accuracy of the standard address base and the personnel information base.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for automatic classification and collection of demographic data according to any of claims 1 to 7.
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| CN117196240A (en) * | 2023-09-21 | 2023-12-08 | 广东省核工业地质局测绘院 | House-ground integrated project-based household registration information acquisition method and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117196240A (en) * | 2023-09-21 | 2023-12-08 | 广东省核工业地质局测绘院 | House-ground integrated project-based household registration information acquisition method and system |
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