POI point aggregation method, electronic device and computer program product

Abstract

The present application discloses a POI point aggregation method, electronic device, and computer program product, relating to the field of geographic information service technology. The POI point aggregation method includes: obtaining POI data of all target POI points in a target area, and obtaining Beidou grid codes of all two-dimensional grids in the target area at a first grid level, wherein the POI data includes the longitude and latitude of the target POI points; determining the attribution relationship between each target POI point and each two-dimensional grid at the first grid level based on the longitude and latitude of each target POI point and the Beidou grid code of each two-dimensional grid at the first grid level; based on the attribution relationship between each target POI point and each two-dimensional grid at the first grid level, aggregating the target POI points in units of two-dimensional grids at the first grid level to obtain all target POI aggregation points at the first grid level. The present application can achieve multi-level, multi-precision POI point aggregation in a unified grid.

Description

Technical Field

[0001] The present application relates to the field of geographic information service technology, and in particular to a POI aggregation method, electronic equipment, and computer program product. Background Art

[0002] In the field of geographic information systems and location-based services, the grid algorithm is a commonly used POI (Point of Interest) aggregation method. By dividing the geographic space into a series of grid cells, it can effectively organize and process a large amount of map point of interest data.

[0003] However, existing grid algorithms face some challenges when processing multi-source heterogeneous data:

[0004] Inconsistent grid levels and sizes: Different data sources often require the creation of grids of different levels and sizes, which leads to incompatibility between grids and increases the difficulty of data integration and analysis.

[0005] Limitations of fixed grid size: Fixed-size grids are inefficient when processing datasets of varying densities. For example, in areas with densely populated areas of interest, smaller grids may not be sufficient to capture sufficient details, while in areas with sparsely populated areas, larger grids may result in wasted resources. Summary of the Invention

[0006] The main purpose of this application is to provide a POI point aggregation method, electronic device and computer program product, aiming to solve the technical problem that the grid algorithm has great limitations in the application of POI point aggregation.

[0007] To achieve the above objectives, the present application provides a POI aggregation method, comprising:

[0008] Obtaining POI data for all target POI points in a target area, and obtaining Beidou grid codes for all two-dimensional grids in the target area at a first grid level, wherein the POI data includes the latitude and longitude of the target POI points;

[0009] Determining, based on the longitude and latitude of each target POI point and the Beidou grid code of each two-dimensional grid under the first grid level, the attribution relationship between each target POI point and each two-dimensional grid under the first grid level;

[0010] Based on the attribution relationship between each target POI point and each two-dimensional grid under the first grid level, the target POI points are aggregated in units of two-dimensional grids under the first grid level to obtain all target POI aggregation points of the target area under the first grid level.

[0011] In one embodiment, the step of determining the attribution relationship between each target POI point and each two-dimensional grid under the first grid level according to the latitude and longitude of each target POI point and the Beidou grid code of each two-dimensional grid under the first grid level includes:

[0012] Decoding the Beidou grid code of each two-dimensional grid at the first grid level to obtain the longitude and latitude range corresponding to each two-dimensional grid at the first grid level;

[0013] According to the longitude and latitude of each target POI point and the longitude and latitude range corresponding to each two-dimensional grid under the first grid level, the belonging relationship between each target POI point and each two-dimensional grid under the first grid level is determined respectively.

[0014] In one embodiment, the step of determining the attribution relationship between each target POI point and each two-dimensional grid under the first grid level according to the latitude and longitude of each target POI point and the Beidou grid code of each two-dimensional grid under the first grid level includes:

[0015] Encode the longitude and latitude of each target POI point according to the first grid level to obtain the Beidou grid code corresponding to each target POI point at the first grid level;

[0016] According to the Beidou grid code of each two-dimensional grid under the first grid level and the Beidou grid code corresponding to each target POI point under the first grid level, the attribution relationship between each target POI point and each two-dimensional grid under the first grid level is determined respectively.

[0017] In one embodiment, the step of obtaining POI data of all target POI points in the target area includes:

[0018] Get the original POI data of all target POI points in the target area;

[0019] The original two-dimensional POI data of each target POI point is preprocessed respectively to obtain the POI data of each target POI point, wherein the preprocessing includes data cleaning, data standardization and coordinate system conversion, and the coordinate system conversion is used to convert the coordinates of the target POI point into a representation by latitude and longitude.

[0020] In one embodiment, after the step of aggregating the target POI points in units of two-dimensional grids at the first grid level based on the attribution relationship between each target POI point and each two-dimensional grid at the first grid level to obtain all target POI aggregation points in the target area at the first grid level, the method further includes:

[0021] After detecting an instruction to perform an aggregation operation on all target POI points in the target area at a second grid level, obtaining Beidou grid codes of all two-dimensional grids in the target area at the second grid level, wherein the second grid level is lower than the first grid level;

[0022] Determining, according to the Beidou grid code of each two-dimensional grid under the first grid level and the Beidou grid code of each two-dimensional grid under the second grid level, an attribution relationship between each two-dimensional grid under the first grid level and each two-dimensional grid under the second grid level;

[0023] According to the attribution relationship between each two-dimensional grid under the second grid level and each two-dimensional grid under the first grid level, the target POI aggregation points under the first grid level are aggregated in units of two-dimensional grids under the second grid level to obtain all target POI aggregation points of the target area under the second grid level.

[0024] In one embodiment, the method further comprises:

[0025] Obtaining the aggregate coordinates and POI aggregate quantity of each target POI aggregation point in the target area at the first grid level;

[0026] Generate visualization icons corresponding to the target POI aggregation points at the aggregation coordinates of the target POI aggregation points at the first grid level, and mark the POI aggregation quantity of each target POI aggregation point at the first grid level in the corresponding visualization icon;

[0027] Among them, the size of the visualization icon is positively correlated with the number of annotated POI aggregations.

[0028] In one embodiment, the method further comprises:

[0029] Obtaining the aggregate coordinates and POI aggregate quantity of each target POI aggregation point in the target area at the first grid level;

[0030] According to the aggregation coordinates of each target POI aggregation point at the first grid level, the POI aggregation quantity of each target POI aggregation point at the first grid level is respectively marked in the two-dimensional grid to which each target POI aggregation point at the first grid level belongs;

[0031] The visualization color of each two-dimensional grid under the first grid level is determined according to the number of POI aggregations marked in each two-dimensional grid under the first grid level and the preset mapping relationship between the number of POI aggregations and the visualization color.

[0032] In one embodiment, the aggregation coordinates of the target POI aggregation point are the centroid coordinates of the two-dimensional grid to which the target POI aggregation point belongs, or the geometric median coordinates of each target POI point in the two-dimensional grid to which the target POI aggregation point belongs.

[0033] In addition, to achieve the above-mentioned purpose, the present application also provides an electronic device, which includes: a memory, a processor, and a POI point aggregation program stored on the memory and runnable on the processor. When the POI point aggregation program is executed by the processor, the steps of the POI point aggregation method as described above are implemented.

[0034] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned POI point aggregation method when executed by a processor.

[0035] The present application provides a POI point aggregation method, electronic device and computer program product. The technical solution of the present application is to first obtain POI data of all target POI points in a target area and obtain Beidou grid codes of all two-dimensional grids in the target area at a first grid level, wherein the POI data includes the longitude and latitude of the target POI point, and then determine the attribution relationship between each target POI point and each two-dimensional grid at the first grid level according to the longitude and latitude of each target POI point and the Beidou grid code of each two-dimensional grid at the first grid level. Finally, based on the attribution relationship between each target POI point and each two-dimensional grid at the first grid level, the target POI points are aggregated in units of two-dimensional grids at the first grid level to obtain all target POI aggregation points in the target area at the first grid level, so that the present application can realize multi-level and multi-precision POI point aggregation of a unified grid to solve the technical problem that grid algorithms have large limitations in the application of POI point aggregation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0038] Figure 1 A schematic diagram of the process flow of the first embodiment of the POI aggregation method of the present application;

[0039] Figure 2 This is a flow chart of the first method of determining the ownership relationship in the POI aggregation method of this application;

[0040] Figure 3 This is a flow chart of the second method of determining the ownership relationship in the POI aggregation method of this application;

[0041] Figure 4 A schematic diagram of the flow chart of the second embodiment of the POI aggregation method of the present application;

[0042] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the POI point aggregation method in the embodiment of the present application.

[0043] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0044] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0045] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0046] Currently, grid algorithms have significant limitations in the application of POI aggregation.

[0047] The main solution of the embodiment of the present application is: obtaining POI data of all target POI points in the target area, and obtaining Beidou grid codes of all two-dimensional grids in the target area at the first grid level, wherein the POI data includes the longitude and latitude of the target POI point; determining the attribution relationship between each target POI point and each two-dimensional grid under the first grid level according to the longitude and latitude of each target POI point and the Beidou grid code of each two-dimensional grid under the first grid level; based on the attribution relationship between each target POI point and each two-dimensional grid under the first grid level, aggregating the target POI points in units of two-dimensional grids under the first grid level to obtain all target POI aggregation points in the target area at the first grid level.

[0048] The embodiments of the present application can achieve multi-level, multi-precision POI point aggregation in a unified grid to solve the technical problem that the grid algorithm has significant limitations in the application of POI point aggregation.

[0049] It should be noted that the execution subject of the embodiments of the present application is an electronic device, which may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs (Televisions) and desktop computers, or any other electronic device capable of implementing the above functions. The embodiments of the present application do not specifically limit this. The following describes the following embodiments of the present application using electronic devices as the execution subject as an example.

[0050] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0051] This application proposes a POI aggregation method according to a first embodiment.

[0052] Please refer to Figure 1 , Figure 1 A flowchart of the first embodiment of the POI aggregation method provided in this application.

[0053] In this embodiment, the POI aggregation method may include steps S100 to S300:

[0054] Step S100 , obtaining POI data of all target POI points in the target area, and obtaining Beidou grid codes of all two-dimensional grids at the first grid level in the target area, wherein the POI data includes the latitude and longitude of the target POI points.

[0055] It should be noted that this embodiment is implemented based on the Beidou grid code system. Those skilled in the art will appreciate that the Beidou grid code system is a coding system used to uniquely identify grids. Based on the geographic reference framework of the Beidou satellite navigation system, it accurately determines the location of each grid. The Beidou grid code system identifies each grid with a unique code (also known as a Beidou grid code), facilitating data retrieval and management.

[0056] Specifically, this embodiment pre-encodes the Beidou grid codes of all two-dimensional grids at multiple grid levels of different resolutions according to the encoding rules of the Beidou grid code encoding system. In actual applications, when the user or system needs to aggregate some POI points in a certain area at a certain grid level, the area can be designated as the target area, the part of the POI points can be designated as the target POI points, and the grid level can be designated as the first grid level, so as to apply the POI aggregation method provided by this embodiment to aggregate the POI points in the area at this grid level.

[0057] It should also be noted that in this embodiment, the higher the grid level, the smaller the actual geographical area corresponding to a single two-dimensional grid at that grid level. POI data refers to the attribute information of a POI point, typically including the name, type, and location (i.e., two-dimensional coordinates) of the POI point.

[0058] In a feasible implementation, the step of obtaining POI data of all target POI points in the target area in step S100 may include steps S110 to S120:

[0059] Step S110, obtaining original POI data of all target POI points in the target area;

[0060] In step S120, the original two-dimensional POI data of each target POI point is preprocessed to obtain the POI data of each target POI point, wherein the preprocessing includes data cleaning, data standardization and coordinate system conversion, and the coordinate system conversion is used to convert the coordinates of the target POI point into a representation by longitude and latitude.

[0061] In this embodiment, the POI data of the target POI point in the target area may be obtained by pre-processing the original POI data of the target POI point.

[0062] It should be noted that, in this embodiment, the original POI data refers to unprocessed POI data directly obtained from the data source, which may have duplication, omission, error, different format, different coordinate system and other issues.

[0063] This implementation uses GIS (Geographic Information System) software or online service interfaces to obtain raw POI data for all target POIs within a target area, including information such as name, type, and 2D coordinates, from authoritative data sources (such as public databases and commercial data providers). This data is then preprocessed to check for outliers, duplicates, and missing values, and cleansed accordingly to reduce noise and improve the accuracy of subsequent analysis. The data format and units are then standardized and converted to the target coordinate system, completing coordinate system 1. This results in POI data for all target POIs within the target area, ensuring data compatibility and accuracy in subsequent processing, providing a foundation for subsequent spatial analysis and aggregation. The target coordinate system is the coordinate system used by the Beidou grid code encoding system, which is also the coordinate system in which the 3D grid resides.

[0064] Step S200, determining the attribution relationship between each target POI point and each two-dimensional grid under the first grid level according to the latitude and longitude of each target POI point and the Beidou grid code of each two-dimensional grid under the first grid level;

[0065] In one possible implementation, Figure 2 As shown, step S200 may include steps S210 to S220:

[0066] Step S210: decoding the Beidou grid code of each two-dimensional grid at the first grid level to obtain the longitude and latitude range corresponding to each two-dimensional grid at the first grid level;

[0067] Step S220 , determining the attribution relationship between each target POI point and each two-dimensional grid in the first grid level according to the longitude and latitude of each target POI point and the longitude and latitude range corresponding to each two-dimensional grid in the first grid level.

[0068] In this embodiment, the Beidou grid code of the two-dimensional grid can be decoded to obtain the longitude and latitude range corresponding to each two-dimensional grid, so that the target POI point whose longitude and latitude are within a certain longitude and latitude range can be determined to belong to the two-dimensional grid corresponding to the longitude and latitude range, and then the attribution relationship between each target POI point and each two-dimensional grid under the first grid level can be determined.

[0069] It should be noted that in this embodiment, there is no overlap in the longitude and latitude ranges corresponding to different two-dimensional grids at the same grid level. For example, when the longitude range corresponding to a two-dimensional grid is [10, 11), the longitude range corresponding to the two-dimensional grid adjacent to the right at the same latitude of the two-dimensional grid is [11, 12), and the longitude range corresponding to the two-dimensional grid adjacent to the left is [9, 10), ensuring that there is no overlap and no gaps between them, so as to avoid the target POI points located on the boundaries of adjacent grids from being unable to determine their ownership.

[0070] In another possible embodiment, Figure 3 As shown, step S200 may further include steps S230 to S240:

[0071] Step S230, encoding the longitude and latitude of each target POI point according to the first grid level to obtain the Beidou grid code corresponding to each target POI point at the first grid level;

[0072] Step S240 , determining the attribution relationship between each target POI point and each two-dimensional grid in the first grid level according to the Beidou grid code of each two-dimensional grid in the first grid level and the Beidou grid code corresponding to each target POI point in the first grid level.

[0073] In this embodiment, the longitude and latitude of the target POI point can also be encoded at the first grid level to obtain the Beidou grid code corresponding to each target POI point at the first grid level, so as to determine that the target POI point belongs to the two-dimensional grid corresponding to its Beidou grid code, and then determine the attribution relationship between each target POI point and each two-dimensional grid at the first grid level.

[0074] Step S300 : Based on the attribution relationship between each target POI point and each two-dimensional grid at the first grid level, the target POI points are aggregated in units of two-dimensional grids at the first grid level to obtain all target POI aggregate points at the first grid level in the target area.

[0075] After determining the attribution relationship between each target POI point and each two-dimensional grid, this embodiment can aggregate the target POI points belonging to the same two-dimensional grid at the first grid level, taking the two-dimensional grid as the unit, to obtain the target POI aggregation point corresponding to the two-dimensional grid, thereby realizing the aggregation processing of all target POI points in the target area at the first grid level.

[0076] Since this embodiment is implemented based on the Beidou grid code encoding system and adopts the unified standard of the Beidou grid code encoding system, all two-dimensional grids are in the same coordinate system, and the two-dimensional grids at the same grid level have the same size and shape, and are all identified by a unique Beidou grid code. There is no overlap or gap between them, and the target area can be completely covered, which can lay a solid foundation for the application of grid algorithms in POI point aggregation, ensuring that when performing POI point aggregation, the grid data of the Beidou grid code encoding system can be used to achieve accurate aggregation, avoid overlap and omission, and effectively solve the defects of existing grid algorithms in the application of POI point aggregation, such as incompatibility between grids and high difficulty in data integration and analysis due to different data sources creating grids of different levels and sizes. At the same time, there is no limitation of fixed grid size, and different grid levels can be flexibly selected as the first grid level for POI point aggregation according to actual needs.

[0077] It should be noted that when aggregating all target POI aggregation points in the target area at the first grid level, a two-dimensional grid can aggregate at most one target POI aggregation point, and when a two-dimensional grid does not have a target POI point belonging to it, the target POI aggregation point cannot be aggregated in the two-dimensional grid, or in other words, the number of POI aggregations corresponding to the target POI aggregation point aggregated by the two-dimensional grid is 0, that is, the target POI aggregation point aggregated by the two-dimensional grid is composed of 0 target POI points.

[0078] In this embodiment, the aggregation coordinates of the target POI aggregation point are the centroid coordinates of the two-dimensional grid to which the target POI aggregation point belongs, or the geometric median coordinates of each target POI point in the two-dimensional grid to which the target POI aggregation point belongs.

[0079] Those skilled in the art will know that the center of mass refers to the average position of the mass distribution of an object (or a system composed of multiple objects), and the geometric median refers to the point with the smallest sum of distances to all points.

[0080] In this embodiment, the centroid coordinates refer to the coordinates of the centroid, and the geometric median coordinates refer to the coordinates of the geometric median.

[0081] In this embodiment, the aggregation coordinates of the target POI aggregation point can be the centroid coordinates of the two-dimensional grid, or the geometric median coordinates of each target POI point in the two-dimensional grid to which it belongs, which is not specifically limited in this embodiment.

[0082] When the aggregation coordinates are taken as the centroid coordinates, the computational complexity of the POI point aggregation process can be greatly simplified. When the geometric median is taken, although the computational complexity is slightly larger, it is still much lower than the POI point aggregation based on the distance algorithm, and can reflect the center position of each target POI point in the two-dimensional grid.

[0083] It should be noted that there is more than one type of POI point. Users can select a specific type of POI point as the target POI point according to the type of POI point, thereby aggregating the specific type of POI points.

[0084] Furthermore, in a feasible implementation, the POI aggregation method may further include steps A10 to A20:

[0085] Step A10, obtaining the aggregate coordinates and POI aggregate quantity of each target POI aggregate point at the first grid level in the target area;

[0086] Step A20: generating a visualization icon corresponding to each target POI aggregation point at the aggregation coordinates of each target POI aggregation point at the first grid level, and marking the POI aggregation number of each target POI aggregation point at the first grid level on the corresponding visualization icon;

[0087] Among them, the size of the visualization icon is positively correlated with the number of annotated POI aggregations.

[0088] In this embodiment, the aggregation coordinates and POI aggregation quantity of each target POI aggregation point will be recorded when POI points are aggregated. Therefore, in subsequent visualization, when the user adjusts the resolution size of the map to the grid level, the aggregation status of the target POI points can be displayed at the aggregation coordinates of each target POI aggregation point in the form of a visualization icon on the map, and the aggregation quantity of each target POI aggregation point can be marked in the corresponding visualization icon, so that the user can understand how many target POI points are aggregated under the target POI aggregation point through the numbers marked in the visualization icon.

[0089] In addition, this embodiment also associates the size of the visualization icon with the number of annotated POI aggregations. When the number of annotated POI aggregations changes, the size of the visualization icon may also change accordingly.

[0090] In another feasible implementation, the POI aggregation method may further include steps B10 to B30:

[0091] Step B10, obtaining the aggregate coordinates and POI aggregate quantity of each target POI aggregate point at the first grid level in the target area;

[0092] Step B20: Marking the POI aggregation quantity of each target POI aggregation point at the first grid level into the two-dimensional grid to which each target POI aggregation point at the first grid level belongs, according to the aggregation coordinates of each target POI aggregation point at the first grid level;

[0093] Step B30 , determining the visualization color of each two-dimensional grid at the first grid level according to the number of POI clusters marked in each two-dimensional grid at the first grid level and a preset mapping relationship between the number of POI clusters and the visualization color.

[0094] In this embodiment, the POI aggregation number of the target POI aggregation point can also be marked in the corresponding two-dimensional grid, and the color of the two-dimensional grid can be changed according to the marked POI aggregation number.

[0095] In one example, the color depth may be changed according to the number of marked POI clusters. The smaller the number of marked POI clusters, the lighter the visualization color of the grid, and vice versa.

[0096] In another example, the number of POI aggregations may be divided into multiple levels, and different levels of POI aggregation numbers correspond to different colors, so that the visualization color of the grid is determined according to the marked number of POI aggregations.

[0097] By marking the number of POI clusters on the two-dimensional grid and changing the grid visualization color, this embodiment can allow users to more intuitively perceive the clustering status of target POI points in each grid.

[0098] Based on the above first embodiment, a POI aggregation method according to a second embodiment of the present application is proposed.

[0099] Please refer to Figure 4 , Figure 4 A flowchart of the second embodiment of the POI aggregation method provided in this application.

[0100] In this embodiment, after step S300, steps S400 to S600 may be further included:

[0101] Step S400: After detecting an instruction to aggregate all target POIs in a target area at a second grid level, obtaining Beidou grid codes of all two-dimensional grids in the target area at the second grid level, wherein the second grid level is lower than the first grid level;

[0102] Step S500: determining, based on the Beidou grid code of each two-dimensional grid in the first grid level and the Beidou grid code of each two-dimensional grid in the second grid level, the attribution relationship between each two-dimensional grid in the first grid level and each two-dimensional grid in the second grid level;

[0103] Step S600: Based on the relationship between each two-dimensional grid at the second grid level and each two-dimensional grid at the first grid level, the target POI aggregation points at the first grid level are aggregated in units of two-dimensional grids at the second grid level to obtain all target POI aggregation points at the second grid level in the target area.

[0104] In this embodiment, in addition to designating a certain grid level as the first grid level and directly aggregating the target POI points in the target area at this grid level, when the target POI aggregation points of the target area at a certain grid level have been aggregated, the grid level can also be used as the first grid level, so that when it is necessary to aggregate the target POI points of the target area at a lower level, the lower level can be used as the second grid level, and then the POI point aggregation method provided by this embodiment is used to aggregate the POI points of the second grid level based on the aggregation results of the first grid level, thereby reducing the calculation amount of POI point aggregation and improving the POI point aggregation efficiency.

[0105] It should be noted that, in this embodiment, among the predefined multiple different grid levels, the two-dimensional grids of the lower level can be composed of multiple two-dimensional grids of the higher level. For example, a two-dimensional grid in the second grid level, when refined to the first grid level, is composed of four adjacent two-dimensional grids in the first grid level.

[0106] In addition, please refer to Figure 5 , Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the POI point aggregation method in the embodiment of the present application.

[0107] The present application also provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the POI point aggregation method in the above embodiment.

[0108] Reference below Figure 5 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic devices in the embodiments of the present application may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs (Televisions), desktop computers, and the like, or any other electronic device capable of implementing the above functions. Figure 5 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0109] like Figure 5 As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory 1002 or programs loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the electronic device. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems may be connected to the input / output interface 1006: an input device 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; a storage device 1003 including, for example, a magnetic tape or hard disk; and a communication device 1009. The communication device 1009 may allow the electronic device to communicate with other devices wirelessly or wired to exchange data. Although the figures show electronic devices with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0110] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0111] The electronic device provided in this application, using the POI aggregation method described in the above-mentioned embodiments, can resolve the technical problem of the significant limitations of grid algorithms in the application of POI aggregation. Compared with the prior art, the beneficial effects of the electronic device provided in this application are the same as those of the POI aggregation method described in the above-mentioned embodiments, and the other technical features of the electronic device are the same as those disclosed in the POI aggregation method described in the above-mentioned embodiments, and are not further described here.

[0112] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0113] In addition, the present application also provides a computer-readable storage medium having computer-readable program instructions (ie, computer program) stored thereon, and the computer-readable program instructions are used to execute the POI aggregation method in the above embodiment.

[0114] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0115] The computer-readable storage medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0116] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by an electronic device, the electronic device is caused to: obtain POI data of all target POI points in a target area, and obtain Beidou grid codes of all two-dimensional grids in the target area at a first grid level, wherein the POI data includes the longitude and latitude of the target POI point; determine the attribution relationship between each target POI point and each two-dimensional grid at the first grid level according to the longitude and latitude of each target POI point and the Beidou grid code of each two-dimensional grid at the first grid level; based on the attribution relationship between each target POI point and each two-dimensional grid at the first grid level, aggregate the target POI points in units of two-dimensional grids at the first grid level to obtain all target POI aggregation points in the target area at the first grid level.

[0117] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0118] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0119] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0120] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned POI aggregation method. This addresses the technical limitations of grid algorithms in the application of POI aggregation. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are similar to those of the POI aggregation method provided in the aforementioned embodiments and are not further elaborated here.

[0121] In addition, an embodiment of the present application further provides a computer program product, including a computer program, which implements the POI point aggregation method in the above embodiment when executed by a processor.

[0122] The computer program product provided in this application can solve the technical problem of the significant limitations of grid algorithms in the application of POI point aggregation. Compared with the prior art, the beneficial effects of the computer program product provided in the embodiments of this application are the same as those of the POI point aggregation method provided in the above embodiments, and will not be repeated here.

[0123] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A POI aggregation method, characterized in that: The method comprises: Obtaining POI data for all target POI points in a target area, and obtaining Beidou grid codes for all two-dimensional grids in the target area at a first grid level, wherein the POI data includes the latitude and longitude of the target POI points; Determining, based on the longitude and latitude of each target POI point and the Beidou grid code of each two-dimensional grid under the first grid level, the attribution relationship between each target POI point and each two-dimensional grid under the first grid level; Based on the attribution relationship between each target POI point and each two-dimensional grid at the first grid level, the target POI points are aggregated in units of two-dimensional grids at the first grid level to obtain all target POI aggregate points in the target area at the first grid level, wherein the aggregate coordinates of the target POI aggregate points are: the coordinates of the geometric median of each target POI point in the two-dimensional grid to which the target POI aggregate point belongs; The step of determining the attribution relationship between each target POI point and each two-dimensional grid under the first grid level according to the longitude and latitude of each target POI point and the Beidou grid code of each two-dimensional grid under the first grid level includes: Decoding the Beidou grid code of each two-dimensional grid under the first grid level to obtain the longitude and latitude range corresponding to each two-dimensional grid under the first grid level; determining the attribution relationship between each target POI point and each two-dimensional grid under the first grid level based on the longitude and latitude of each target POI point and the longitude and latitude range corresponding to each two-dimensional grid under the first grid level; or Encoding the longitude and latitude of each target POI point according to the first grid level to obtain a Beidou grid code corresponding to each target POI point at the first grid level; determining the attribution relationship between each target POI point and each two-dimensional grid at the first grid level based on the Beidou grid code of each two-dimensional grid at the first grid level and the Beidou grid code corresponding to each target POI point at the first grid level; The method further comprises: After detecting an instruction to perform an aggregation operation on all target POI points in the target area at a second grid level, obtaining Beidou grid codes of all two-dimensional grids in the target area at the second grid level, wherein the second grid level is lower than the first grid level; Determining, according to the Beidou grid code of each two-dimensional grid under the first grid level and the Beidou grid code of each two-dimensional grid under the second grid level, an attribution relationship between each two-dimensional grid under the first grid level and each two-dimensional grid under the second grid level; According to the attribution relationship between each two-dimensional grid under the second grid level and each two-dimensional grid under the first grid level, the target POI aggregation points under the first grid level are aggregated in units of two-dimensional grids under the second grid level to obtain all target POI aggregation points of the target area under the second grid level.

2. The POI aggregation method according to claim 1, wherein: The step of obtaining POI data of all target POI points in the target area includes: Get the original POI data of all target POI points in the target area; The original two-dimensional POI data of each target POI point is preprocessed respectively to obtain the POI data of each target POI point, wherein the preprocessing includes data cleaning, data standardization and coordinate system conversion, and the coordinate system conversion is used to convert the coordinates of the target POI point into a representation by latitude and longitude.

3. The POI aggregation method according to claim 1, wherein: The method further comprises: Obtaining the aggregate coordinates and POI aggregate quantity of each target POI aggregation point in the target area at the first grid level; Generate visualization icons corresponding to the target POI aggregation points at the aggregation coordinates of the target POI aggregation points at the first grid level, and mark the POI aggregation quantity of each target POI aggregation point at the first grid level in the corresponding visualization icon; Among them, the size of the visualization icon is positively correlated with the number of annotated POI aggregations.

4. The POI aggregation method according to claim 1, wherein: The method further comprises: Obtaining the aggregate coordinates and POI aggregate quantity of each target POI aggregation point in the target area at the first grid level; According to the aggregation coordinates of each target POI aggregation point at the first grid level, the POI aggregation quantity of each target POI aggregation point at the first grid level is respectively marked in the two-dimensional grid to which each target POI aggregation point at the first grid level belongs; The visualization color of each two-dimensional grid under the first grid level is determined according to the number of POI aggregations marked in each two-dimensional grid under the first grid level and the preset mapping relationship between the number of POI aggregations and the visualization color.

5. An electronic device, characterized in that: include: A memory, a processor, and a POI aggregation program stored in the memory and executable on the processor, wherein the POI aggregation program, when executed by the processor, implements the steps of the POI aggregation method according to any one of claims 1 to 4.

6. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the POI aggregation method according to any one of claims 1 to 4 are implemented.

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