CN115545807B - Business district dividing method and device, geographic information system, terminal equipment and medium - Google Patents
Business district dividing method and device, geographic information system, terminal equipment and medium Download PDFInfo
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Abstract
The invention discloses a business circle dividing method, a business circle dividing device, a geographic information system, terminal equipment and a medium, wherein the method comprises the following steps: acquiring the type of a target business district and geographic information data of a target area; wherein the geographic information data comprises AOI data and POI data; clustering AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type region; screening POI data which are not contained in any area of the first type from the POI data corresponding to the target business district type to serve as POI data to be divided; clustering the POI data to be divided by adopting the preset clustering algorithm to obtain at least one second type area; and combining the first type area and the second type area to obtain a target business district area corresponding to the target business district type. By adopting the embodiment of the invention, the division of business circles can be effectively realized.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a business district dividing method and device, a geographic information system, terminal equipment and a medium.
Background
The business circle is centered on the local store location and extends in a certain direction, so that the purpose of attracting more customers is achieved. The development potential and diversified business category of a business circle greatly drive the economic development in the whole range, and great convenience is brought to the life of people. The establishment of the business circles plays an important role in promoting the balanced development of the regions, but the inventor finds that the traditional business circles are custom made and have no definite boundary, and no algorithm is used for defining the division of the business circles, so that the establishment of the business circles is adversely affected.
Disclosure of Invention
The embodiment of the invention provides a business area division method, a business area division device, a geographic information system, terminal equipment and a medium, which can effectively realize business area division.
An embodiment of the present invention provides a business turn dividing method, including:
acquiring the type of a target business district and geographic information data of a target area; wherein the geographic information data comprises AOI data and POI data;
clustering the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type region;
screening POI data which are not contained in any area of the first type from the POI data corresponding to the target business district type to serve as POI data to be divided;
clustering the POI data to be partitioned by adopting the preset clustering algorithm to obtain at least one second type region;
and combining the area of the first type and the area of the second type to obtain a target business area corresponding to the target business area type.
As an improvement of the above scheme, the geographic information data further includes road network information;
the clustering is performed on the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type of region, and the method specifically comprises the following steps:
performing administrative region division on the target region according to the road network information to obtain a plurality of administrative region blocks;
clustering AOI data corresponding to the target business district type in each administrative region block by adopting a preset clustering algorithm to obtain a first type region corresponding to each administrative region block;
for an administrative region block comprising a plurality of regions of a first type, calculating the area of each region of the first type of the administrative region block, and aggregating the regions of the first type with the area smaller than a preset threshold value by taking the preset threshold value as an upper area limit;
and obtaining a first type of region corresponding to each administrative region block after the aggregation is finished.
As an improvement of the above scheme, the geographic information data further includes road network information;
after the combining the first type region and the second type region to obtain the target business district region corresponding to the target business district type, the method further includes:
determining the area of a road block, the quantity of AOIs and the quantity of POIs corresponding to each target business district according to the geographic information data;
and determining the number of target business district areas with the POI coverage rate within a preset range according to the POI data corresponding to the target business district type.
As an improvement of the above scheme, after the combining the first type region and the second type region to obtain the target business district region corresponding to the target business district type, the method further includes:
acquiring crowd image characteristic information in each target business district;
and carrying out characteristic analysis according to the crowd portrait characteristic information, the AOI data and the POI data in each target business district to obtain a characteristic label of each target business district.
As an improvement of the above scheme, the preset clustering algorithm includes:
extracting data points which are not extracted from the data currently used for clustering;
judging whether the number of data points in the data for clustering currently and the number of data points in a preset distance threshold value of the data points extracted currently are not less than a preset number, if so, extracting data points with direct density reaching from the data points extracted currently from the data for clustering currently to perform clustering to obtain an area of a corresponding type, and entering the next step, otherwise, directly entering the next step;
and judging whether the data points which are not extracted exist in the data which are currently used for clustering, if so, returning to the step of extracting the data points which are not extracted from the data which are currently used for clustering, and if not, finishing clustering.
Accordingly, another embodiment of the present invention provides a business district dividing apparatus, including:
the data acquisition module is used for acquiring the type of a target business district and the geographic information data of a target area; wherein the geographic information data comprises AOI data and POI data;
the AOI clustering module is used for clustering the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type region;
the POI screening module is used for screening POI data which are not contained in any area of the first type from the POI data corresponding to the target business district type to serve as POI data to be divided;
the POI clustering module is used for clustering the POI data to be partitioned by adopting the preset clustering algorithm to obtain at least one second type region;
and the region merging module is used for merging the region of the first type and the region of the second type to obtain a target business district region corresponding to the target business district type.
Correspondingly, another embodiment of the invention provides a geographic information system, which comprises a database component, a map component, a business district dividing component and a display component; wherein, the first and the second end of the pipe are connected with each other,
the database component is used for storing geographic information data of a map;
the map component is used for carrying out map visualization according to the geographic information data;
the business circle dividing component is used for executing the business circle dividing method according to any one of the above items when being triggered, and outputting an execution result to the display component; the triggering condition of the business circle dividing component comprises that geographic information data corresponding to the target area in the database component is updated;
and the display component is used for displaying the execution result of the business district dividing component.
As an improvement of the above scheme, the geographic information system further comprises a billboard drawing component;
the billboard drawing component is used for receiving a billboard drawing instruction aiming at a target area and input by a user, and drawing the visual billboard of the target area correspondingly according to the billboard drawing instruction.
Accordingly, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the business turn dividing method as described in any one of the above items when executing the computer program.
Accordingly, another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program runs, the apparatus on which the computer-readable storage medium is located is controlled to execute the business turn dividing method according to any one of the above items.
Compared with the prior art, the business turn dividing method, the business turn dividing device, the geographic information system, the terminal device and the medium disclosed by the embodiment of the invention have the advantages that for the target area, at least one area of a first type is obtained by clustering AOI data corresponding to the type of the target business turn, so that the target business turn is drawn preliminarily, POI data corresponding to the type of the target business turn which is not contained in the area of the first type are clustered, so that at least one area of a second type is obtained, so that the target business turn is supplemented, and the areas of the first type and the areas of the second type are merged to filter out repeated areas in the two clustered areas, so that the target business turn area in the target area can be obtained, and the business turn dividing is realized.
Drawings
Fig. 1 is a schematic flow chart of a business circle dividing method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a business circle dividing apparatus according to an embodiment of the present invention;
FIG. 3 is a block diagram of a geographic information system according to an embodiment of the present invention;
FIG. 4 is a schematic illustration of a presentation interface of a geographic information system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Fig. 1 is a schematic flow chart of a business turn dividing method according to an embodiment of the present invention.
An embodiment of the present invention provides a business district dividing method, including:
s11, acquiring the type of a target business district and geographic information data of a target area; wherein the geographic information data comprises AOI data and POI data.
In the present embodiment, the types of business circles include life circles, shopping circles, work circles, leisure circles, and the like. The target business district type can be one or more of the types, so that a plurality of types of business district areas can be divided simultaneously or only one type of business district area can be divided. In specific implementation, the target business district type may be specified in advance, or the user sends a business district dividing instruction including the target business district type when needed, so as to obtain the target business district type. It should be noted that AOI refers to Area of Interest, i.e., a plane of Interest. POI refers to Point of interest, i.e., a Point of interest. The AOI and the POI comprise four items of basic information of name, address, category and longitude and latitude coordinates,
illustratively, the geographic information data of the target area, including contour access, road access, AOI access, POI access, may be pulled from a database, which returns data in a geometrically recognizable text format for columns with geographic locations.
In an optional embodiment, after the step S11, a data format conversion may be performed on the geographic information data, for example, the csv file is converted into a shp format, the shp format can store geometric entities of elements, store geometric positions of spatial objects such as streets, road networks, cells, and the like, and the shp file may also store attributes of the spatial objects, so as to facilitate subsequent division of a business district.
S12, clustering the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type region.
It should be noted that the AOI data and the POI data are classified according to a certain rule, and each type of business circles has the AOI data and the POI data of the corresponding classes. For example, AOI data corresponding to a life circle is a residential community AOI, and POI data corresponding to a life circle is a life-related POI, which specifically includes: fresh fruits, mother and infant services, business halls, hairdressing and beauty, pet services, photographic print shops, laundries, clinics, living markets, logistics express deliveries, intermediary services, markets, kindergartens, schools, drug stores, hospitals and the like; the AOI data corresponding to the shopping circle are a shopping mall AOI and a pedestrian street AOI, and the POI data corresponding to the shopping circle selects a shopping related POI, and specifically comprises the following steps: matching retail business, professional wholesale market, retail professional marketplace, travel business, walking street, food city, supermarket, monopoly store, digital home appliance, clothing shoe bag, home building material, cosmetics retail, jewelry, sports outdoor, convenience store, cinema and the like; the AOI data that work circle corresponds include industry garden type AOI and office building type AOI, and the POI data that work circle corresponds is work related type POI, specifically includes: office buildings, companies, and the like which are not available in the industrial park type AOI and the office building type AOI; the AOI data that the leisure circle corresponds include tourist attraction type AOI and culture venue type AOI, and the POI data that the leisure circle corresponds is leisure amusement type POI, specifically includes: bathing, massaging and pedicure, game halls, KTV, internet bars, scenic spots, park squares and the like. In specific implementation, AOI data and POI data corresponding to the target business district type can be selected according to the category of each AOI and POI so as to perform cluster analysis.
In this step, the preset clustering algorithm may be K-means, DBscan, hierarchical clustering, or the like, or may be other clustering algorithms, which is not limited herein. By taking the type of the target business circle as a life circle as an example, the method may include taking a street boundary as a center, pressing a residential cell type AOI (with a boundary range) as a core AOI, clustering according to a specified number of cells and a mutual distance between center points, and performing region frame selection on each clustered cluster after clustering to obtain at least one region of a first type.
By clustering the AOI data corresponding to the target business district type, the AOI data in the same business district can be gathered as much as possible, and the AOI data in different business districts are separated as much as possible, so that the business district division accuracy is improved.
S13, screening POI data which are not contained in any area of the first type from the POI data corresponding to the target business district type to serve as POI data to be divided.
In this step, POIs not included in the first type of area are filtered for subsequent areas of a business district.
And S14, clustering the POI data to be partitioned by adopting the preset clustering algorithm to obtain at least one second type region.
In this step, the living related POIs (no boundary range) not included in the first type of area may be clustered according to the number of the designated related POIs and the mutual distances between the POIs to obtain at least one second type of area.
S15, combining the first type area and the second type area to obtain a target business district area corresponding to the business district type.
In this step, all the first type regions and all the second type regions are compared, and if the first type regions and the second type regions overlap, the first type regions and the second type regions are combined, so that an accurate target business area is obtained.
As one optional embodiment, the geographic information data further includes road network information;
the clustering is performed on the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type of area, and the method specifically comprises the following steps:
s121, performing administrative region division on the target region according to the road network information to obtain a plurality of administrative region blocks;
s122, clustering AOI data corresponding to the target business district type in each administrative region block by adopting a preset clustering algorithm to obtain a first type region corresponding to each administrative region block;
s123, for an administrative region block comprising a plurality of regions of the first type, calculating the area of each region of the first type of the administrative region block, and aggregating the regions of the first type with the area smaller than a preset threshold value by taking the preset threshold value as an upper area limit;
and S124, obtaining a first type of region corresponding to each administrative region block after the aggregation is completed.
In this embodiment, the road network contour is cut according to the road network information, and the cut road blocks are separated, so as to facilitate subsequent clustering. And then, selecting AOI data corresponding to the target business district type for clustering, judging the area of each first type of area after clustering, if the area is larger than or equal to a preset threshold value, considering the area as a business district corresponding to the target business district type, if the area is smaller than the preset threshold value, considering the area not enough to form a business district, taking the convex hull center of the area smaller than the preset threshold value as the center, and aggregating AOI in administrative district blocks to ensure that the upper limit of the area of the formed circle reaches the preset threshold value, and gradually clustering. It should be noted that the preset threshold may be set according to actual requirements, and is not limited herein. Optionally, the preset threshold is 0.2km 2 。
As one optional embodiment, the geographic information data further includes road network information;
after the combining the first type area and the second type area to obtain the target business area corresponding to the target business area type, the method further includes:
determining the area of a road block, the quantity of AOIs and the quantity of POIs corresponding to each target business district according to the geographic information data;
and determining the number of target business district areas with the POI coverage rate within a preset range according to the POI data corresponding to the target business district type.
In this embodiment, the area of the road block where the divided target business circle is located is calculated, and the number of AOIs and POIs and the number of business circle areas where the POI coverage rate corresponding to the type of the target business circle is within a preset range are calculated, so that the statistics of the feature data of the business circle is realized.
As one optional embodiment, after the combining the first type region and the second type region to obtain the target business district region corresponding to the target business district type, the method further includes:
acquiring the characteristic information of the crowd image in each target business district;
and carrying out characteristic analysis according to the crowd portrait characteristic information, the AOI data and the POI data in each target business district to obtain a characteristic label of each target business district.
Illustratively, the feature analysis model may be trained in advance through the crowd sketch feature information, AOI data and POI data of the feature labeled business circles, so that feature labels of different business circle regions can be obtained through analysis by the feature analysis model.
In the embodiment, by further analyzing the characteristic labels of the business district areas, the types of the business districts can be specified, and the development of the business districts can be purposefully promoted.
As an optional embodiment, the preset clustering algorithm includes:
s21, extracting data points which are not extracted from the data used for clustering;
s22, judging whether the number of data points, within a preset distance threshold, of the data for clustering currently and the currently extracted data points is not less than a preset number, if so, extracting the data points, of which the density can reach directly from the currently extracted data points, from the data for clustering currently to perform clustering to obtain a region of a corresponding type, and entering a next step S23, otherwise, directly entering the next step S23;
and S23, judging whether the data points which are not extracted exist in the data which are currently used for clustering, if so, returning to the step of extracting the data points which are not extracted from the data which are currently used for clustering (namely step S21), and if not, finishing clustering.
It should be noted that, in this embodiment, when the AOI data corresponding to the target business district type is clustered, the current data used for clustering is the AOI data corresponding to the target business district type, and the clustering result is a first type region; when the POI data to be divided are clustered, the data used for clustering at present are the POI data to be divided, and the clustering result is an area of a second type.
In this embodiment, direct density reachable means that sample q is in the Eps neighborhood of sample p.
Accordingly, referring to fig. 2, another embodiment of the present invention provides a business turn dividing apparatus, including:
the data acquisition module 31 is used for acquiring the type of the target business district and the geographic information data of the target area; wherein the geographic information data comprises AOI data and POI data;
the AOI clustering module 32 is configured to cluster AOI data corresponding to the target business district type by using a preset clustering algorithm to obtain at least one first type region;
the POI screening module 33 is configured to screen POI data that are not included in any of the first type of area from the POI data corresponding to the target business district type, so as to serve as POI data to be divided;
the POI clustering module 34 is configured to cluster the POI data to be partitioned by using the preset clustering algorithm to obtain at least one second type region;
and the region merging module 35 is configured to merge the region of the first type and the region of the second type to obtain a target business district region corresponding to the target business district type.
As an improvement of the above scheme, the geographic information data further includes road network information;
the AOI clustering module 32 is specifically configured to:
performing administrative region division on the target region according to the road network information to obtain a plurality of administrative region blocks;
respectively clustering AOI data corresponding to the target business district type in each administrative region block by adopting a preset clustering algorithm to obtain a first type region corresponding to each administrative region block;
for an administrative region block comprising a plurality of regions of a first type, calculating the area of each region of the first type of the administrative region block, and aggregating the regions of the first type with the area smaller than a preset threshold value by taking the preset threshold value as an upper area limit;
and obtaining a first type of region corresponding to each administrative region block after the aggregation is finished.
As an improvement of the above scheme, the geographic information data further includes road network information;
the device further comprises a data statistics module, wherein the data statistics module is specifically configured to:
determining the area of the road block, the AOI number and the POI number corresponding to each target business district according to the geographic information data;
and determining the number of target business district areas with the POI coverage rate within a preset range according to the POI data corresponding to the target business district type.
As an improvement of the above scheme, the apparatus further includes a tag analysis module, and the tag analysis module is specifically configured to:
acquiring the characteristic information of the crowd image in each target business district;
and performing characteristic analysis according to the crowd portrait characteristic information, the AOI data and the POI data in each target business area region to obtain a characteristic label of each target business area region.
As an improvement of the above scheme, the preset clustering algorithm includes:
extracting data points which are not extracted from the data currently used for clustering;
judging whether the number of data points in the data for clustering currently and the number of data points in a preset distance threshold value of the data points extracted currently are not less than a preset number, if so, extracting data points with direct density reaching from the data points extracted currently from the data for clustering currently to perform clustering to obtain an area of a corresponding type, and entering the next step, otherwise, directly entering the next step;
and judging whether the data points which are not extracted exist in the data which are currently used for clustering, if so, returning to the step of extracting the data points which are not extracted from the data which are currently used for clustering, and if not, finishing clustering.
Accordingly, referring to fig. 3, another embodiment of the present invention provides a geographic information system, comprising a database component 41, a map component 42, a business turn division component 43, and a presentation component 44; wherein the content of the first and second substances,
the database component 41 is used for storing geographic information data of a map;
the map component 42 is configured to perform map visualization according to the geographic information data;
the business turn dividing component 43 is configured to execute the business turn dividing method according to any of the above embodiments when triggered, and output an execution result to the display component 44; wherein the trigger condition of the business district dividing component 43 includes that the geographic information data corresponding to the target area in the database component 41 is updated;
the display component 44 is configured to display an execution result of the business turn dividing component 43.
In this embodiment, after the operation of the algorithm model, the relevant data of the target business district can be connected to the geographic information system for display, the dimensions such as the size of human mouth, the thermal power of the model, the portrait of people and the like are screened according to the requirements of different scenes, and the business district distribution condition of the city under the condition can be observed after the query.
The map component 42 may divide the city into 450 meters by 450 meters grids, and the AOI number is calculated by the size of the designated grid, so that the geographic information system may perform grid screening according to the needs, including basic and business states, and condition types including population scale, model heating power, crowd portrayal, consumption capability, brand distribution, grid types, and the like, and may display the corresponding grid area on the map by querying after screening.
In this embodiment, the triggering condition of the business turn dividing component 43 may be that geographic information data corresponding to the target area in the database component 41 is updated, when information such as a geographic location, a street, a road network, and the like is adjusted, coordinates, contours, and access numbers of corresponding AOI/POIs also change, and the business turn dividing component 43 re-clusters and re-iterates the AOI/POIs to update business turn information, thereby implementing optimization. In addition, the trigger condition of the business turn dividing component 43 may also include receiving a business turn dividing instruction of the user or reaching a preset period, which is not limited herein.
As an improvement of the above solution, the geographic information system further comprises a billboard drawing component 45;
the kanban drawing component 45 is configured to receive a kanban drawing instruction for a target area input by a user, and correspondingly draw a visual kanban in the target area according to the kanban drawing instruction.
In this embodiment, the geographic information data may further include information such as city area, population size (residential population, working population, etc.), population image, and economic data (average population GDP, industrial GDP, etc.). After receiving the signboard drawing instruction of the user, the signboard drawing component 45 may draw a visual signboard of a total area production value, a retail amount of social consumer goods, a distribution situation of a website and the like according to the geographic information data, and display dimensions such as a population scale, model heating power, a crowd image, economic data and the like. Therefore, the geographic information system can not only divide the business circle of the city, but also survey indexes such as city economy, population and development, show the total production value, development trend and network distribution condition of the city in a billboard mode, realize transverse comparison with commercial potentials of other cities through a radar map, send screening results to designated people, realize sharing, contribute to reasonable layout of the commercial property, better and accurately capture the demands of customers, position the operation type and scale of the brand of the business circle, and provide guidance for business circle operation and brand entrance. As shown in fig. 4, the geographic information system can display a map in the target area, business area (circled portion in the map), names of business circles, resident population, working population and the like.
Fig. 5 is a schematic diagram of a terminal device according to an embodiment of the present invention.
The terminal device provided by the embodiment of the present invention includes a processor 51, a memory 52, and a computer program stored in the memory 52 and configured to be executed by the processor 51, where the processor 51 implements the business turn division method according to any one of the above embodiments when executing the computer program.
The processor 51, when executing the computer program, implements the steps in the embodiment of the business turn dividing method described above, for example, all the steps of the business turn dividing method shown in fig. 1. Alternatively, the processor 51, when executing the computer program, implements the functions of the modules/units in the aforementioned embodiments of the business turn dividing apparatus, for example, the functions of the modules of the business turn dividing apparatus shown in fig. 2.
Illustratively, the computer program may be partitioned into one or more modules that are stored in the memory 52 and executed by the processor 51 to implement the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which are used for describing the execution process of the computer program in the terminal device. For example, the computer program may be divided into an acquisition module, a measurement module, a calculation module and a comparison module, and the specific functions of each module are as follows: the data acquisition module is used for acquiring the type of a target business district and the geographic information data of a target area; wherein the geographic information data comprises AOI data and POI data; the AOI clustering module is used for clustering the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type region; the POI screening module is used for screening POI data which are not contained in any area of the first type from the POI data corresponding to the target business district type to serve as POI data to be divided; the POI clustering module is used for clustering the POI data to be partitioned by adopting the preset clustering algorithm to obtain at least one second type area; and the region merging module is used for merging the region of the first type and the region of the second type to obtain a target business district region corresponding to the target business district type.
The terminal device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The terminal device may include, but is not limited to, a processor 51, a memory 52. It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a terminal device and does not constitute a limitation of the terminal device, and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the terminal device may also include input output devices, network access devices, buses, etc.
The Processor 51 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. The general processor may be a microprocessor or the processor may be any conventional processor or the like, and the processor 51 is the control center of the terminal device and connects the various parts of the whole terminal device by using various interfaces and lines.
The memory 52 can be used for storing the computer programs and/or modules, and the processor 51 implements various functions of the terminal device by running or executing the computer programs and/or modules stored in the memory 52 and calling data stored in the memory 52. The memory 52 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the terminal device, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the terminal device integrated module/unit can be stored in a computer readable storage medium if it is implemented in the form of software functional unit and sold or used as an independent product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection therebetween, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
Compared with the prior art, the business turn dividing method, the business turn dividing device, the geographic information system, the terminal device and the medium disclosed by the embodiment of the invention have the advantages that for the target area, at least one area of a first type is obtained by clustering AOI data corresponding to the type of the target business turn, so that the target business turn is drawn preliminarily, POI data corresponding to the type of the target business turn which is not contained in the area of the first type are clustered, so that at least one area of a second type is obtained, so that the target business turn is supplemented, and the areas of the first type and the areas of the second type are merged to filter out repeated areas in the two clustered areas, so that the target business turn area in the target area can be obtained, and the business turn dividing is realized.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (9)
1. A business turn dividing method is characterized by comprising the following steps:
acquiring the type of a target business district and geographic information data of a target area; wherein the geographic information data comprises AOI data and POI data;
clustering AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type region;
screening POI data which are not contained in any area of the first type from the POI data corresponding to the target business district type to serve as POI data to be divided;
clustering the POI data to be divided by adopting the preset clustering algorithm to obtain at least one second type area;
combining the first type area and the second type area to obtain a target business district area corresponding to the target business district type;
the geographic information data further comprises road network information;
the clustering is performed on the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type of region, and the method specifically comprises the following steps:
performing administrative region division on the target region according to the road network information to obtain a plurality of administrative region blocks;
clustering AOI data corresponding to the target business district type in each administrative region block by adopting a preset clustering algorithm to obtain a first type region corresponding to each administrative region block;
for an administrative region block comprising a plurality of regions of a first type, calculating the area of each region of the first type of the administrative region block, and aggregating the regions of the first type with the area smaller than a preset threshold value by taking the preset threshold value as an upper area limit;
and obtaining a first type of region corresponding to each administrative region block after the aggregation is finished.
2. The business circle dividing method according to claim 1, wherein said geographic information data further includes road network information;
after the combining the first type region and the second type region to obtain the target business district region corresponding to the target business district type, the method further includes:
determining the area of the road block, the AOI number and the POI number corresponding to each target business district according to the geographic information data;
and determining the number of target business district areas with the POI coverage rate in a preset range according to the POI data corresponding to the target business district type.
3. The business turn dividing method according to claim 1, wherein after said combining the first type area and the second type area to obtain a target business turn area corresponding to the target business turn type, the method further comprises:
acquiring crowd image characteristic information in each target business district;
and performing characteristic analysis according to the crowd portrait characteristic information, the AOI data and the POI data in each target business area region to obtain a characteristic label of each target business area region.
4. The quotient circle dividing method of claim 1, wherein said predetermined clustering algorithm comprises:
extracting data points which are not extracted from the data currently used for clustering;
judging whether the number of data points in the data for clustering currently and the number of data points in a preset distance threshold value of the data points extracted currently are not less than a preset number, if so, extracting data points with direct density reaching from the data points extracted currently from the data for clustering currently to perform clustering to obtain an area of a corresponding type, and entering the next step, otherwise, directly entering the next step;
and judging whether the data points which are not extracted exist in the data which are currently used for clustering, if so, returning to the step of extracting the data points which are not extracted from the data which are currently used for clustering, and if not, finishing clustering.
5. A business turn dividing apparatus, comprising:
the data acquisition module is used for acquiring the type of a target business district and the geographic information data of a target area; wherein the geographic information data comprises AOI data and POI data;
the AOI clustering module is used for clustering the AOI data corresponding to the target business district type by adopting a preset clustering algorithm to obtain at least one first type region;
the POI screening module is used for screening POI data which are not contained in any area of the first type from the POI data corresponding to the target business district type to be used as POI data to be divided;
the POI clustering module is used for clustering the POI data to be partitioned by adopting the preset clustering algorithm to obtain at least one second type area;
the region merging module is used for merging the region of the first type and the region of the second type to obtain a target business district region corresponding to the target business district type;
the geographic information data further comprises road network information;
the AOI clustering module is specifically configured to:
performing administrative region division on the target region according to the road network information to obtain a plurality of administrative region blocks;
clustering AOI data corresponding to the target business district type in each administrative region block by adopting a preset clustering algorithm to obtain a first type region corresponding to each administrative region block;
for an administrative region block comprising a plurality of regions of a first type, calculating the area of each region of the first type of the administrative region block, and aggregating the regions of the first type with the area smaller than a preset threshold value by taking the preset threshold value as an upper area limit;
and obtaining a first type of region corresponding to each administrative region block after the aggregation is finished.
6. A geographic information system is characterized by comprising a database component, a map component, a business district dividing component and a display component; wherein the content of the first and second substances,
the database component is used for storing geographic information data of a map;
the map component is used for carrying out map visualization according to the geographic information data;
the business circle dividing component is used for executing the business circle dividing method according to any one of claims 1-4 when triggered and outputting an execution result to the display component; the triggering condition of the business circle dividing component comprises that geographic information data corresponding to the target area in the database component is updated;
and the display component is used for displaying the execution result of the business district dividing component.
7. The geographic information system of claim 6 further comprising a billboard-rendering component;
the billboard drawing component is used for receiving a billboard drawing instruction aiming at a target area and input by a user, and drawing the visual billboard of the target area correspondingly according to the billboard drawing instruction.
8. A terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the quotient circle division method according to any one of claims 1 to 4 when executing the computer program.
9. A computer-readable storage medium, comprising a stored computer program, wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the business turn dividing method according to any one of claims 1 to 4.
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| CN111985514A (en) * | 2019-05-23 | 2020-11-24 | 顺丰科技有限公司 | Business circle identification method and device, electronic equipment and storage medium |
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| CN108242203A (en) * | 2016-12-23 | 2018-07-03 | 中兴通讯股份有限公司 | A kind of region partitioning method and device |
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| CN111932318B (en) * | 2020-09-21 | 2021-01-19 | 腾讯科技（深圳）有限公司 | Region division method and device, electronic equipment and computer readable storage medium |
| CN115018536A (en) * | 2022-05-30 | 2022-09-06 | 维沃移动通信有限公司 | Region determination method and device, electronic equipment and readable storage medium |
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| CN115204273A (en) * | 2022-06-23 | 2022-10-18 | 广西中烟工业有限责任公司 | Method and device for classifying customers based on business district big data and electronic equipment |
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