CN112328725A - Dividing device and method for enterprise geographic position attribution area based on map data - Google Patents
Dividing device and method for enterprise geographic position attribution area based on map data Download PDFInfo
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Abstract
The device firstly splits the geoJson data of a target area into the geoJson data of each sub-area by utilizing the characteristic that the geoJson data of one area contains the latitude and longitude range interval of the area, and then determines which sub-area of the target area the target enterprise belongs to through latitude matching, thereby realizing the purpose of accurately dividing the area of the enterprise and providing great convenience for the analysis of the data of the follow-up enterprise. In addition, the application also provides a method, equipment and a readable storage medium for dividing the enterprise geographic position attribution area based on the map data, and the technical effect of the method and the equipment corresponds to that of the device.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a device, a method, an apparatus, and a readable storage medium for dividing an enterprise geographic location attribution area based on map data.
Background
With the increase of the number of enterprises, in the process of business analysis, it is necessary to acquire the location information of the enterprises, and form a structural data based on region division for the enterprise data. How to perform regional division on an enterprise, guarantee division precision and improve subsequent enterprise information analysis effect is a problem to be solved urgently by technical personnel in the field.
Disclosure of Invention
The application aims to provide a dividing device, a dividing method, a dividing device and a readable storage medium for an enterprise geographic position attribution area based on map data, and the dividing device, the dividing method, the dividing device and the readable storage medium are used for solving the problem that the analysis effect of enterprise data is influenced because no scheme for accurately dividing the area where an enterprise is located exists at present. The specific scheme is as follows:
in a first aspect, the present application provides a device for dividing an enterprise geographic location home region based on map data, including:
a data acquisition module: the method comprises the steps of obtaining geoJson data of a target area, wherein the geoJson data comprise latitude and longitude range intervals, and the target area comprises a plurality of sub-areas;
a data splitting module: the geoJson data of the target area are split to obtain the geoJson data of each sub-area;
a matching module: and the system is used for matching the longitude and latitude data of the target enterprise with the geoJson data of each sub-area respectively to determine the target sub-area to which the target enterprise belongs.
Preferably, the data splitting module includes a plurality of stages of data splitting units, and each stage of data splitting unit is configured to further split the sub-region obtained by splitting the previous stage of data splitting unit.
Preferably, the data splitting module includes:
and (3) saving a splitting unit: the geoJson data of the target area are split to obtain the geoJson data of each province;
a market splitting unit: the method comprises the steps of splitting the geoJson data of the province to obtain the geoJson data of each city;
a region splitting unit: the method comprises the steps of splitting geoJson data of the city to obtain the geoJson data of each region;
the street split unit: and splitting the geoJson data of the region to obtain the geoJson data of each street.
Preferably, the matching module includes a plurality of stages of matching units, and each stage of matching unit is configured to further match the target sub-region obtained by matching with the previous stage of matching unit.
Preferably, the matching module includes:
a provincial matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each province in a target area;
market matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each city in a target province;
a region matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each region in a target city;
a street matching unit: and the system is used for matching the longitude and latitude data of the target enterprise with the geoJson data of each street in the target area respectively to determine the target street to which the target enterprise belongs.
Preferably, the method further comprises the following steps:
a label setting module: the location tag is configured to set a location tag for the target enterprise according to a target sub-region to which the target enterprise belongs, where the location tag includes: province labels, city labels, district labels, street labels.
Preferably, the method further comprises the following steps:
a table generation module: generating a corresponding region structure table according to the geoJson data of the sub-regions, wherein the region structure table comprises the following fields: ID, area name, ID of the previous table, level.
In a second aspect, the present application provides a method for dividing an enterprise geographic location home region based on map data, including:
acquiring geoJson data of a target area, wherein the geoJson data comprises a longitude and latitude range interval, and the target area comprises a plurality of sub-areas;
splitting the geoJson data of the target area to obtain the geoJson data of each sub-area;
and matching the longitude and latitude data of the target enterprise with the geoJson data of each sub-area respectively to determine the target sub-area to which the target enterprise belongs.
In a third aspect, the present application provides a device for dividing an enterprise geographic location home region based on map data, including:
a memory: for storing a computer program;
a processor: for executing the computer program to implement the dividing method of the enterprise geographic position home region based on the map data.
In a fourth aspect, the present application provides a readable storage medium having stored thereon a computer program, which when executed by a processor, is configured to implement the method for dividing a geographical location home zone of an enterprise based on map data as described above.
The dividing device for the enterprise geographic position attribution area based on the map data comprises a data acquisition module, a data splitting module and a matching module, wherein the data acquisition module is used for acquiring geoJson data of a target area, the geoJson data comprises a longitude and latitude range interval, and the target area comprises a plurality of sub-areas; the data splitting module is used for splitting the geoJson data of the target area to obtain the geoJson data of each sub-area; the matching module is used for matching the longitude and latitude data of the target enterprise with the geoJson data of each sub-area respectively and determining the target sub-area to which the target enterprise belongs.
Therefore, the device utilizes the characteristic that the geoJson data of one area comprises the latitude and longitude range interval of the area, firstly splits the geoJson data of the target area into the geoJson data of each sub-area, and then determines which sub-area of the target area the target enterprise belongs to through latitude matching, so that the purpose of accurately dividing the area of the enterprise is achieved, and great convenience is provided for the data analysis of the follow-up enterprise.
In addition, the application also provides a method, equipment and a readable storage medium for dividing the enterprise geographic position attribution area based on the map data, and the technical effect of the method, the equipment and the readable storage medium corresponds to the technical effect of the device, and the details are not repeated here.
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For a clearer explanation of the embodiments or technical solutions of the prior art of the present application, the drawings needed for the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a functional block diagram of a first embodiment of a device for dividing an enterprise geographic location home region based on map data according to the present application;
fig. 2 is a functional block diagram of a second embodiment of a dividing apparatus for dividing an enterprise geographic location home region based on map data according to the present application;
FIG. 3 is a flowchart of an embodiment of a method for dividing an enterprise geographic location home region based on map data according to the present disclosure;
fig. 4 is a block diagram of an embodiment of a device for dividing an enterprise geographic location home region based on map data according to the present application.
Detailed Description
The core of the application is to provide a dividing device, a dividing method, a dividing device and a readable storage medium for the enterprise geographic position attribution area based on map data, and the purpose of accurately dividing the area where the enterprise is located is achieved by utilizing the characteristic that the geoJson data of one area contains the latitude and longitude range interval of the area, so that great convenience is provided for the subsequent enterprise data analysis.
In order that those skilled in the art will better understand the disclosure, the following detailed description will be given with reference to the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, a first embodiment of a device for dividing an enterprise geographic location home area based on map data according to the present application is described below, where the first embodiment includes:
the data acquisition module 10: the method comprises the steps of obtaining geoJson data of a target area, wherein the geoJson data comprise latitude and longitude range intervals, and the target area comprises a plurality of sub-areas;
the main purpose of this embodiment is to divide the attribution area of the geographical location of the enterprise based on the map data, and then label the geographical location to the enterprise, for example, the location of the enterprise can be marked by location attributes such as province, city, district, street, etc., which is convenient for data cleaning and later application based on address location.
The geoJson is a format that encodes various geographic data structures, including types, elements (features), which include multidimensional arrays that include latitude and longitude range intervals for regions. In practical application, the specific longitude and latitude data can be matched with the longitude and latitude range, so that whether an enterprise corresponding to the longitude and latitude data is in the area or not can be judged.
The data splitting module 11: the geoJson data of the target area are split to obtain the geoJson data of each sub-area;
the matching module 12: and the system is used for matching the longitude and latitude data of the target enterprise with the geoJson data of each sub-area respectively to determine the target sub-area to which the target enterprise belongs.
Specifically, the longitude and latitude data of the target enterprise are compared with the longitude and latitude range interval in the geoJson data of each sub-area, whether the longitude and latitude data are located in the longitude and latitude range interval is judged, and if yes, the target enterprise is judged to belong to the corresponding sub-area.
The process of splitting the geoJson data of the target region once to obtain the geoJson data of each sub-region is described above. In practical application, the geoJson data of the target area can be split for multiple times for meeting scene requirements or improving efficiency. At this moment, the data splitting module specifically comprises a plurality of stages of data splitting units, and each stage of data splitting unit is used for further splitting the sub-region obtained by splitting the previous stage of data splitting unit. For example, assuming that the data splitting module specifically includes two stages of data splitting units, the first stage data splitting unit is configured to split the geoJson data of the target region to obtain the geoJson data of each first stage sub-region (sub-region of the target region); the secondary data splitting unit is used for splitting the geoJson data of the primary sub-area to obtain the geoJson data of each secondary sub-area (sub-area of the primary sub-area).
It can be understood that, when the data splitting module includes a plurality of stages of data splitting units, in order to improve the matching efficiency, the matching module may also include a plurality of stages of matching units, and each stage of matching unit is configured to further match a target sub-region obtained by matching with a previous stage of matching unit. For example, if the data splitting module includes two stages of data splitting units, the matching module also includes two stages of matching units, where the first stage matching unit is configured to match the longitude and latitude data of the target enterprise with the longitude and latitude range intervals of the first stage sub-areas, and determine the target first stage sub-area to which the target enterprise belongs; the second-level matching unit is used for matching the longitude and latitude data of the target enterprise with the longitude and latitude range interval of each second-level sub-area in the target first-level sub-area, and determining the target second-level sub-area to which the target enterprise belongs.
As a specific implementation manner, in practical application, this embodiment may further include a tag setting module, where the tag setting module is configured to set a location tag for the target enterprise according to a target sub-area to which the target enterprise belongs. It is understood that when the data splitting module includes a plurality of levels of data splitting units, the location tag of the enterprise is also a plurality of levels, for example, when the data splitting module includes a plurality of levels of data splitting units, the geoJson data is split into a provincial geoJson data, a city geoJson data, a district geoJson data, and a street geoJson data, respectively, then the location tag of the enterprise includes a province tag, a city tag, a district tag, and a street tag.
In order to improve matching efficiency, in the process of processing the geoJson data, the geoJson data may be analyzed first, and description modes of attributes such as positions of the geoJson data are normalized.
In addition, after the geoJson data are split, key information can be extracted from the splitting result, and a form of a table is generated, so that the matching efficiency is further improved.
The embodiment provides a dividing device of an enterprise geographic position attribution area based on map data, which comprises a data acquisition module, a data splitting module and a matching module. According to the device, the characteristic that the geoJson data of one area contain the latitude and longitude range interval of the area is utilized, the geoJson data of the target area are firstly split into the geoJson data of each sub-area, and then the sub-area of the target area to which the target enterprise belongs is determined through latitude matching, so that the purpose of accurately dividing the area where the enterprise is located is achieved, and great convenience is brought to the data analysis of the follow-up enterprise.
It can be understood that the device can ensure that the corresponding regions are matched for the enterprises, and the accuracy is extremely high due to the fact that region division is carried out on the basis of the same piece of geoJson data, and the device can be used in a unified mode and has complete verification logic.
An embodiment of a second device for dividing an enterprise geographic location home area based on map data provided by the present application is described in detail below, and referring to fig. 2, the embodiment second specifically includes:
the data acquisition module 20: the method comprises the steps of obtaining nationwide geoJson data, wherein the geoJson data comprises longitude and latitude range intervals;
the data splitting module 21: the method comprises the steps of splitting the nationwide geoJson data to obtain the geoJson data of each sub-region;
firstly, analyzing the data format of the geojson data, and dividing the geojson data of the whole country into the geojson data of each province, the geojson data of each city, the geojson data of each district and the geojson data of each street step by step through code segmentation. And adding hierarchical information for each splitting result, and uploading to a file server.
The table generation module 22: the method comprises the steps of generating a corresponding region structure table according to geoJson data of the sub-region;
specifically, key information in the geoJson data is extracted, and a basic region structure table is generated. The region structure table contains the following fields: ID, level, ID of the upper-level table, area name, and the following information is contained in the area structure table: the area name of each sub-area in the current area and the latitude and longitude range interval of each sub-area.
Wherein, the "ID" refers to the ID of the current area structure table, and is used for distinguishing different area structure tables; "level" means the level at which the current regional structure table is located, wherein level 1 represents province, level 2 represents city, level 3 represents county or district, and level 4 represents street; "ID of the previous table" refers to ID of the previous area structure table, and is used for maintaining the relationship between the upper and lower levels; the "area name" refers to an area name of the current area structure table, and includes location information such as province, city, district, and street.
Assuming a region structure table is generated from the geoJson data in hangzhou city, the outside of the region structure table contains the following fields: table ID, level 2, ID of the zone structure table in zhejiang province, zone name is hangzhou city in zhejiang province, china; the area structure table contains the following information: the name of each region in Hangzhou city and the latitude and longitude range interval of each region.
The latitude and longitude acquisition module 23: and the method is used for crawling longitude and latitude data of the target enterprise to be subjected to area division and storing the data into an enterprise table.
In practical application, all enterprises in a certain range can be designated as target enterprises, and longitude and latitude data of all enterprises in the range is crawled and stored in an enterprise table. Wherein, the fields of the enterprise table include: business ID, business name, latitude of registration (lon field), latitude of registration (lat field), and may further include: registration number, organizational code, business status, registered capital, industry, business type, etc.
The matching module 24: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring the geoJson data of each sub-region and the longitude and latitude data of a target enterprise respectively;
specifically, the geojson data includes a FeatureCollection object, which includes a plurality of multi polygon objects, each of which is equivalent to a province, a city, or a district, each of which includes a coordinates object, which includes a four-dimensional array therein, and which mainly stores latitude and longitude data of a boundary of an area. The innermost layer of array is a coordinate point, the outer layer of array represents how many longitude and latitude points are along the x axis, the outer layer of array represents how many longitude and latitude points are along the y axis, one such three-dimensional array represents the boundary of an area, and the four-dimensional array composed of a plurality of three-dimensional arrays represents the combination of the boundaries of a plurality of surfaces and is used for representing the latitude and longitude range interval.
In practical application, whether the enterprise is in the range interval is judged according to the data points of the longitude and the latitude, and if so, other attribute information of the MultiPolygon object, such as name codes, regions of the multiPolygon object, latitude and longitude, is extracted. Of course, province information is stored when the geojson data of the city is generated in the previous period, and the attributes of the province, the city and the like are recorded when the geojson data of the county is generated.
The label setting module 25: the location tag is configured to set a location tag for the target enterprise according to a target sub-region to which the target enterprise belongs, where the location tag includes: province labels, city labels, district labels, street labels.
Whether the target enterprise is located in a certain sub-area or not is sequentially judged according to the longitude and latitude data of the target enterprise, so that the geoJson data corresponding to the target enterprise is obtained, and the geoJson data contain position information and can correspond to the streets of the province and city, so that the target enterprise can be marked with a position label.
Wherein the data splitting module 21 includes:
and (3) saving a splitting unit: the geoJson data of the target area are split to obtain the geoJson data of each province;
a market splitting unit: the method comprises the steps of splitting the geoJson data of the province to obtain the geoJson data of each city;
a region splitting unit: the method comprises the steps of splitting geoJson data of the city to obtain the geoJson data of each region;
the street split unit: and splitting the geoJson data of the region to obtain the geoJson data of each street.
Correspondingly, the matching module 24 includes:
a provincial matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each province in a target area;
market matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each city in a target province;
a region matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each region in a target city;
a street matching unit: and the system is used for matching the longitude and latitude data of the target enterprise with the geoJson data of each street in the target area respectively to determine the target street to which the target enterprise belongs.
Therefore, according to the dividing device for the enterprise geographic position attribution area based on the map data, the key information of the geoJson data is extracted to generate the basic area structure table, and the geoJson where the enterprise is located is judged according to the longitude and latitude data. The position table analyzed by the geoJson data can correspond to the city and province streets, so that position labels can be marked for enterprises, and the subsequent display statistical analysis of enterprise information is facilitated.
In the following, a method for dividing an enterprise geographic location attribution area based on map data provided by an embodiment of the present application is introduced, and the method for dividing an enterprise geographic location attribution area based on map data described below is implemented based on the above-described device for dividing an enterprise geographic location attribution area based on map data.
As shown in fig. 3, the method for dividing the enterprise geographic location home area based on the map data of the embodiment includes:
s30, acquiring geoJson data of a target area, wherein the geoJson data comprises a longitude and latitude range interval, and the target area comprises a plurality of sub-areas;
s31, splitting the geoJson data of the target area to obtain the geoJson data of each sub-area;
and S32, matching the longitude and latitude data of the target enterprise with the geoJson data of each sub-region respectively, and determining the target sub-region to which the target enterprise belongs.
The method for dividing the geographical location belonging area of the enterprise based on the map data according to this embodiment is implemented based on the above-described apparatus for dividing the geographical location belonging area of the enterprise based on the map data, and therefore, a specific implementation of the method can be found in the foregoing embodiment section of the apparatus for dividing the geographical location belonging area of the enterprise based on the map data, and a description thereof will not be provided here.
In addition, since the dividing method of the geographical location attribution area of the enterprise based on the map data of the embodiment is implemented based on the dividing device of the geographical location attribution area of the enterprise based on the map data described above, the function of the dividing method corresponds to the function of the dividing device, and the description is omitted here.
In addition, the present application also provides a dividing device for an enterprise geographic location home region based on map data, as shown in fig. 4, including:
the memory 100: for storing a computer program;
the processor 200: for executing the computer program to implement the dividing method of the enterprise geographic position home region based on the map data.
Finally, the present application provides a readable storage medium having stored thereon a computer program for implementing, when executed by a processor, the method for dividing a geographical location home zone of an enterprise based on map data as described above.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above detailed descriptions of the solutions provided in the present application, and the specific examples applied herein are set forth to explain the principles and implementations of the present application, and the above descriptions of the examples are only used to help understand the method and its core ideas of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. An apparatus for dividing an enterprise geographic location home region based on map data, comprising:
a data acquisition module: the method comprises the steps of obtaining geoJson data of a target area, wherein the geoJson data comprise latitude and longitude range intervals, and the target area comprises a plurality of sub-areas;
a data splitting module: the geoJson data of the target area are split to obtain the geoJson data of each sub-area;
a matching module: and the system is used for matching the longitude and latitude data of the target enterprise with the geoJson data of each sub-area respectively to determine the target sub-area to which the target enterprise belongs.
2. The apparatus of claim 1, wherein the data splitting module comprises multiple stages of data splitting units, and each stage of data splitting unit is configured to further split a sub-region split by a previous stage of data splitting unit.
3. The apparatus of claim 2, wherein the data splitting module comprises:
and (3) saving a splitting unit: the geoJson data of the target area are split to obtain the geoJson data of each province;
a market splitting unit: the method comprises the steps of splitting the geoJson data of the province to obtain the geoJson data of each city;
a region splitting unit: the method comprises the steps of splitting geoJson data of the city to obtain the geoJson data of each region;
the street split unit: and splitting the geoJson data of the region to obtain the geoJson data of each street.
4. The apparatus of claim 2, wherein the matching module comprises a plurality of stages of matching units, each stage of matching unit is configured to further match a target sub-region matched by a previous stage of matching unit.
5. The apparatus of claim 4, wherein the matching module comprises:
a provincial matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each province in a target area;
market matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each city in a target province;
a region matching unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring longitude and latitude data of a target enterprise and geoJson data of each region in a target city;
a street matching unit: and the system is used for matching the longitude and latitude data of the target enterprise with the geoJson data of each street in the target area respectively to determine the target street to which the target enterprise belongs.
6. The apparatus of claim 5, further comprising:
a label setting module: the location tag is configured to set a location tag for the target enterprise according to a target sub-region to which the target enterprise belongs, where the location tag includes: province labels, city labels, district labels, street labels.
7. The apparatus of any one of claims 1-6, further comprising:
a table generation module: generating a corresponding region structure table according to the geoJson data of the sub-regions, wherein the region structure table comprises the following fields: ID, area name, ID of the previous table, level.
8. A method for dividing an enterprise geographic position home region based on map data is characterized by comprising the following steps:
acquiring geoJson data of a target area, wherein the geoJson data comprises a longitude and latitude range interval, and the target area comprises a plurality of sub-areas;
splitting the geoJson data of the target area to obtain the geoJson data of each sub-area;
and matching the longitude and latitude data of the target enterprise with the geoJson data of each sub-area respectively to determine the target sub-area to which the target enterprise belongs.
9. An apparatus for dividing an enterprise geographic location home region based on map data, comprising:
a memory: for storing a computer program;
a processor: for executing the computer program for implementing the method for dividing a geographical location home zone of an enterprise based on map data as claimed in claim 8.
10. A readable storage medium, having stored thereon a computer program which, when being executed by a processor, is adapted to carry out the method of map data based segmentation of an enterprise geographical location home area of claim 8.
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| CN115237862A (en) * | 2022-08-30 | 2022-10-25 | 四川省交通勘察设计研究院有限公司 | KML file-based map visual display method and device |
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