CN112115221A - Multi-factor matching fusion method for block data - Google Patents
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- 238000004364 calculation method Methods 0.000 claims description 3
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Abstract
The invention discloses a multi-factor matching fusion method of block data, which is used for realizing interconnection and sharing of data in a region and comprises the following steps of S1: the method comprises the steps of establishing an urban area grading method, clustering through geographic data and geographic objects which have incidence relations with the geographic data, dividing an urban space range into a plurality of urban areas based on clustering results, analyzing and establishing a standardized area grading coding system through collecting and counting geographic information of each urban area. The invention discloses a multi-factor matching fusion method for block data, which integrates data of various fields by taking a city or a community as a unit, breaks a data island, realizes interconnection and sharing of data in an area, solves the problem of data monopoly and difficulty in circulation among departments, and provides technical support for realizing scientific and accurate decision.
Description
Technical Field
The invention belongs to the technical field of data matching fusion, and particularly relates to a multi-factor matching fusion method for block data.
Background
The world is entering an era dominated by data, and as a high-level form of big data development, the application of block data is becoming the trend of the era. The block data breaks through data islands and data monopolies existing in point data and strip data, and is a new data view. Unlike directional aggregation of pieces of data, block data is a continuous aggregation of highly correlated classes of data on a particular platform. In the field of social governance, block data is the synthesis of various data relating to people, things and objects formed in administrative areas, and the construction of the block data is to integrate the data of all lines in units of cities, communities and grids. And realizing interconnection and sharing of data in the region.
Due to the weak foundation of early system informatization, distributed storage and difficulty in realizing interconnection and intercommunication among systems. Department data are difficult to exchange and share in a larger range, so that data in a certain field become isolated islands. The department data has single dimensionality and closure, the data is monopolized by a few departments and is difficult to open and circulate, the social development rule is difficult to grasp only by the data in a single field, and scientific and accurate decision making is difficult to realize.
Disclosure of Invention
The invention mainly aims to provide a multi-factor matching fusion method for block data, which integrates data of various fields by taking a city or a community as a unit, breaks a data isolated island, realizes interconnection and sharing of data in an area, solves the problems of data monopoly and difficulty in circulation among departments, and provides technical support for realizing scientific and accurate decision.
In order to achieve the above object, the present invention provides a method for matching and fusing multiple factors of block data, which is used for realizing interconnection and sharing of data in a region, and comprises the following steps:
step S1: establishing an urban area grading method, clustering geographic data and geographic objects having an incidence relation with the geographic data, dividing an urban space range into a plurality of urban areas based on a clustering result, analyzing and establishing a standardized area grading coding system by collecting and counting geographic information (particularly, names of places of the urban areas) of the urban areas (related to business data of all lines);
step S2: establishing integration of a data resource library, accessing (each) data source (including sensing data of resources, working data of each management department, various data on a network and the like, such as a main patent database and a base database) of a (smart) city area through a big data acquisition platform, and accessing the data source into a data cache region through a data access region in a batch non-real-time or stream data real-time calculation mode;
step S3: collecting and counting population data of each collecting position in the urban space range in different time periods, aggregating the population data to form population big data, and establishing association between the population data of the collecting position and the population data of the geographic object in the urban space range in different time periods based on the geographic data.
As a further preferable embodiment of the above technical means, step S1 is specifically implemented as the following steps:
step S1.1: collecting place name statistical data (of departments such as public security, civil administration and statistics) of the urban area, and integrating all place names of the urban area through the statistical data;
step S1.2: establishing a place name database of the urban area based on the integrated place names, and matching virtual information of the place name database with entity information of the urban area;
step S1.3: and establishing an index system for classifying, grading and coding the place names of the urban areas based on the integrated place names.
As a further preferred embodiment of the above technical solution, step S1.3 is specifically implemented as the following steps:
step S1.3.1: the basic geographic information systems of all industries of the urban area are controlled by the urban area polygons to search and position in the urban basic space frame information sharing data set;
step S1.3.2: forming a basic address unit by taking a space unit point, a space unit line and a space unit surface in a basic geographic information system as a basis;
step S1.3.3: coding according to the address unit to form corresponding address information;
step S1.3.4: the address information is used as an index and is connected with a (other) place name database, so that the space positioning of the address information is realized, and the address information and the space information are converted in a bidirectional mode.
As a further preferable embodiment of the above technical means, step S2 is specifically implemented as the following steps:
step S2.1: establishing a special subject database (comprising houses, organizations, places, resources, events and the like) based on a basic geographic information system and a regional hierarchical coding system;
step S2.2: establishing a base map database (the base map database is a standard map base map and related map layers including data of roads, rivers, railways, parks and the like);
step S2.3: the data cache region temporarily stores incremental data of a data source of the urban area, and standard data are obtained after cleaning, mapping and converting the incremental data (all data need to be subjected to data benchmarking with a data standard and are changed into standard data, cleaning, mapping and converting operations only aim at the data in the data cache region and cannot generate any influence on the original data source), and the standard data are stored in a standard data resource library.
As a further preferable embodiment of the above technical means, step S3 is specifically implemented as the following steps:
step S3.1: the standard data resource library associates and integrates standard data according to basic elements (human, land, affairs, things, enterprises and other core elements) of the urban area to form a basic element library;
step S3.2: the basic element database and the special subject database form a basic element data resource pool for external service and sharing;
step S3.3: and performing uniform resource cataloging on the data of the basic element data resource pool to form a basic element data catalog for external sharing and service.
In order to achieve the above object, the present invention further 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 implements the steps of the block data multi-factor matching fusion method when executing the program.
To achieve the above object, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a block data multi-factor matching fusion method.
Detailed Description
The following description is presented to disclose the invention so as to enable any person skilled in the art to practice the invention. The preferred embodiments in the following description are given by way of example only, and other obvious variations will occur to those skilled in the art. The basic principles of the invention, as defined in the following description, may be applied to other embodiments, variations, modifications, equivalents, and other technical solutions without departing from the spirit and scope of the invention.
In a preferred embodiment of the present invention, those skilled in the art should note that the electronic device and the non-transitory computer-readable storage medium, etc., to which the present invention relates may be regarded as prior art.
Preferred embodiments.
The invention discloses a multi-factor matching fusion method of block data, which is used for realizing interconnection and sharing of data in a region and comprises the following steps:
step S1: establishing an urban area grading method, clustering geographic data and geographic objects having an incidence relation with the geographic data, dividing an urban space range into a plurality of urban areas based on a clustering result, analyzing and establishing a standardized area grading coding system by collecting and counting geographic information (particularly, names of places of the urban areas) of the urban areas (related to business data of all lines);
step S2: establishing integration of a data resource library, accessing (each) data source (including sensing data of resources, working data of each management department, various data on a network and the like, such as a main patent database and a base database) of a (smart) city area through a big data acquisition platform, and accessing the data source into a data cache region through a data access region in a batch non-real-time or stream data real-time calculation mode;
step S3: collecting and counting population data of each collecting position in the urban space range in different time periods, aggregating the population data to form population big data, and establishing association between the population data of the collecting position and the population data of the geographic object in the urban space range in different time periods based on the geographic data.
Specifically, step S1 is implemented as the following steps:
step S1.1: collecting place name statistical data of the urban area, and integrating all place names of the urban area through the statistical data;
step S1.2: establishing a place name database of the urban area based on the integrated place names, and matching virtual information of the place name database with entity information of the urban area;
step S1.3: and establishing an index system for classifying, grading and coding the place names of the urban areas based on the integrated place names.
More specifically, step S1.3 is embodied as the following steps:
step S1.3.1: the basic geographic information systems of all industries of the urban area are controlled by the urban area polygons to search and position in the urban basic space frame information sharing data set;
step S1.3.2: forming a basic address unit by taking a space unit point, a space unit line and a space unit surface in a basic geographic information system as a basis;
step S1.3.3: coding according to the address unit to form corresponding address information;
step S1.3.4: the address information is used as an index and is connected with a (other) place name database, so that the space positioning of the address information is realized, and the address information and the space information are converted in a bidirectional mode.
Further, step S2 is specifically implemented as the following steps:
step S2.1: establishing a special subject database (comprising houses, organizations, places, resources, events and the like) based on a basic geographic information system and a regional hierarchical coding system;
step S2.2: establishing a base map database (the base map database is a standard map base map and related map layers including data of roads, rivers, railways, parks and the like);
step S2.3: the data cache region temporarily stores incremental data of a data source of the urban area, and standard data are obtained after cleaning, mapping and converting the incremental data (all data need to be subjected to data benchmarking with a data standard and are changed into standard data, cleaning, mapping and converting operations only aim at the data in the data cache region and cannot generate any influence on the original data source), and the standard data are stored in a standard data resource library.
Further, step S3 is implemented as the following steps:
step S3.1: the standard data resource library associates and integrates standard data according to basic elements of the urban area to form a basic element library;
step S3.2: the basic element database and the special subject database form a basic element data resource pool for external service and sharing;
step S3.3: and performing uniform resource cataloging on the data of the basic element data resource pool to form a basic element data catalog for external sharing and service.
The invention also discloses an electronic device, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of the multi-factor matching fusion method of the block data when executing the program.
The invention also discloses a non-transitory computer-readable storage medium on which a computer program is stored which, when executed by a processor, implements the steps of a block data multi-factor matching fusion method.
It should be noted that the technical features of the electronic device and the non-transitory computer readable storage medium related to the present patent application should be regarded as the prior art, and the specific structure, the operation principle, the control mode and the spatial arrangement mode of the technical features may be selected conventionally in the field, and should not be regarded as the inventive point of the present patent, and the present patent is not further specifically described in detail.
It will be apparent to those skilled in the art that modifications and equivalents may be made in the embodiments and/or portions thereof without departing from the spirit and scope of the present invention.
Claims (7)
1. A multi-factor matching fusion method for block data is used for realizing interconnection and sharing of data in a region, and is characterized by comprising the following steps:
step S1: establishing an urban area grading method, clustering geographic data and geographic objects having an incidence relation with the geographic data, dividing an urban space range into a plurality of urban areas based on a clustering result, analyzing and establishing a standardized area grading coding system by collecting and counting geographic information of each urban area;
step S2: establishing integration of a data resource library, accessing a data source of a city area through a big data acquisition platform, and enabling the data source to enter a data cache region through a data access region in a batch non-real-time or stream data real-time calculation mode;
step S3: collecting and counting population data of each collecting position in the urban space range in different time periods, aggregating the population data to form population big data, and establishing association between the population data of the collecting position and the population data of the geographic object in the urban space range in different time periods based on the geographic data.
2. The method for multi-factor matching fusion of block data according to claim 1, wherein step S1 is implemented as the following steps:
step S1.1: collecting place name statistical data of the urban area, and integrating all place names of the urban area through the statistical data;
step S1.2: establishing a place name database of the urban area based on the integrated place names, and matching virtual information of the place name database with entity information of the urban area;
step S1.3: and establishing an index system for classifying, grading and coding the place names of the urban areas based on the integrated place names.
3. The method for multi-factor matching fusion of block data according to claim 2, wherein step S1.3 is implemented as the following steps:
step S1.3.1: the basic geographic information systems of all industries of the urban area are controlled by the urban area polygons to search and position in the urban basic space frame information sharing data set;
step S1.3.2: forming a basic address unit by taking a space unit point, a space unit line and a space unit surface in a basic geographic information system as a basis;
step S1.3.3: coding according to the address unit to form corresponding address information;
step S1.3.4: the address information is used as an index and is connected with a place name database, so that the space positioning of the address information is realized, and the address information and the space information are converted in a bidirectional mode.
4. The method for multi-factor matching fusion of block data according to claim 3, wherein the step S2 is implemented as the following steps:
step S2.1: establishing a thematic database based on a basic geographic information system and a regional hierarchical coding system;
step S2.2: establishing a base map database;
step S2.3: the data cache region temporarily stores incremental data of a data source of the urban region, the incremental data are cleaned, mapped and converted to obtain standard data, and the standard data are stored in a standard data resource library.
5. The method for multi-factor matching fusion of block data according to claim 4, wherein the step S3 is implemented as the following steps:
step S3.1: the standard data resource library associates and integrates standard data according to basic elements of the urban area to form a basic element library;
step S3.2: the basic element database and the special subject database form a basic element data resource pool for external service and sharing;
step S3.3: and performing uniform resource cataloging on the data of the basic element data resource pool to form a basic element data catalog for external sharing and service.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of a block data multi-factor matching fusion method according to any one of claims 1 to 5 when executing the program.
7. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of a block data multi-factor matching fusion method according to any one of claims 1 to 5.
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