Reverse geocoding data generation method and device, equipment, medium and program product
By hierarchical classification and clustering of interest points in inverse geocoding technology, the problem of inaccurate search for interest points in remote areas is solved, and the accuracy and efficiency of inverse geocoding services are improved.
Patent Information
- Application Number
- CN202411304564.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-18
- Publication Date
- 2025-01-10
AI Technical Summary
The current inverse geocoding technology is not accurate enough when searching for points of interest near geographical coordinates in remote areas, resulting in the inaccurate recognition results of the points of interest returned by the service.
By classifying the interest points in the target area into high-level and low-level according to the inverse geographic service level to which they belong, clustering the low-level interest points, filter out representative interest points, and generate inverses based on the high-level interest points. Geocoded data.
It improves the accuracy of interest points near geographical coordinates in remote areas, improves the service effect of inverse geocoding services, reduces the amount of calculation and manpower investment, and improves data generation efficiency.
Smart Images
Figure CN119293323A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of geocoding technology, and in particular to a method, device, equipment, medium and program product for generating reverse geocoding data. Background Art
[0002] Reverse geocoding is a process of converting geographic coordinates (such as longitude and latitude) into human-readable addresses or place names. Furthermore, the converted human-readable addresses or place names can be used to identify and locate nearby POIs (Point of Interest), and the data information of the found points of interest can be further displayed. Reverse geocoding technology can effectively find points of interest near geographic coordinates, providing users with convenient geographic location services.
[0003] However, the points of interest currently found using reverse geocoding technology are not accurate enough, especially when the geographic coordinates are located in remote areas where the points of interest are sparse. Therefore, it is urgent to provide a solution that can improve the accuracy of the obtained points of interest. Summary of the invention
[0004] The embodiments of the present application provide a method, apparatus, device, medium and program product for generating reverse geocoding data, so as to improve the accuracy of points of interest near acquired geographic coordinates and improve the service effect of reverse geocoding services.
[0005] In a first aspect, an embodiment of the present application provides a method for generating reverse geocoding data, comprising:
[0006] Get multiple points of interest in the target area;
[0007] Based on the attribute information respectively corresponding to the multiple points of interest, determine the reverse geographic service levels respectively corresponding to the multiple points of interest, and classify the multiple points of interest into a first point of interest and a second point of interest according to their respective reverse geographic service levels, the first point of interest corresponds to a first reverse geographic service level, the second point of interest corresponds to a second reverse geographic service level, and the first reverse geographic service level is higher than the second reverse geographic service level;
[0008] For a plurality of second points of interest belonging to a second inverse geographic service level, clustering the plurality of second points of interest according to their locations, and determining a target second point of interest from the plurality of second points of interest after the clustering process;
[0009] The first point of interest and the target second point of interest are used to generate reverse geocoding data of the target area.
[0010] In a possible implementation, clustering the plurality of second interest points according to their locations, and determining a target second interest point from the plurality of second interest points after the clustering process, includes:
[0011] Clustering the plurality of second interest points according to their locations to obtain a clustering result, wherein the clustering result includes cluster clusters and / or noise points;
[0012] If the clustering result includes a cluster but does not include a noise point, selecting a representative second interest point from a plurality of second interest points included in the cluster, and determining the representative second interest point as a target second interest point;
[0013] If the clustering result includes a noise point but does not include a clustering cluster, determining the noise point as a target second interest point;
[0014] If the clustering result includes clusters and noise points, a representative second interest point is selected from the plurality of second interest points included in the clusters, and the representative second interest point and the noise point are determined as the target second interest point.
[0015] In a possible implementation, the selecting a representative second point of interest from the plurality of second points of interest included in the cluster includes:
[0016] Based on the attribute information respectively corresponding to the plurality of second interest points included in the cluster and the weight coefficient corresponding to each attribute information, determine the reverse geography service degree values respectively corresponding to the plurality of second interest points included in the cluster, wherein the reverse geography service degree values are used to measure the friendliness of the reverse geocoding service provided to the user as the reverse geocoding data;
[0017] Based on the inverse geographic service level values respectively corresponding to the plurality of second interest points included in the cluster, a second interest point with the largest inverse geographic service level value is selected from the plurality of second interest points included in the cluster as the representative second interest point.
[0018] In a possible implementation, the attribute information includes regional affiliation information, and the clustering of the plurality of second points of interest according to their locations to obtain a clustering result includes:
[0019] Based on the regional belonging information respectively corresponding to the plurality of second points of interest, determining the administrative regions to which the plurality of second points of interest respectively belong, and grouping the plurality of second points of interest according to the administrative regions to which they belong, to obtain second points of interest corresponding to different groups;
[0020] For any group of second interest points, a plurality of second interest points in the group are clustered according to their locations to obtain clustering results corresponding to different groups.
[0021] In a possible implementation, determining the inverse geographic service levels corresponding to the multiple points of interest respectively based on the attribute information corresponding to the multiple points of interest respectively includes:
[0022] Determining the inverse geographic service degree values corresponding to the plurality of interest points respectively based on the attribute information respectively corresponding to the plurality of interest points and the weight coefficient corresponding to each attribute information;
[0023] Compare the inverse geographic service degree values respectively corresponding to the plurality of interest points with a preset inverse geographic service threshold to obtain comparison results respectively corresponding to the plurality of interest points;
[0024] Based on the comparison results respectively corresponding to the multiple points of interest, the reverse geographic service levels respectively corresponding to the multiple points of interest are determined.
[0025] In a possible implementation, clustering the plurality of second interest points according to their locations includes:
[0026] A density-based spatial clustering algorithm with noise is used to perform clustering processing on the plurality of second interest points.
[0027] In a second aspect, an embodiment of the present application provides a reverse geocoding data generation device, including:
[0028] An acquisition module, used to acquire multiple points of interest in a target area;
[0029] a classification module, configured to determine, based on the attribute information respectively corresponding to the plurality of interest points, the inverse geographic service levels respectively corresponding to the plurality of interest points, and classify the plurality of interest points into a first interest point and a second interest point according to the inverse geographic service levels to which they belong, wherein the first interest point corresponds to the first inverse geographic service level, the second interest point corresponds to the second inverse geographic service level, and the first inverse geographic service level is higher than the second inverse geographic service level;
[0030] A clustering module, configured to cluster the plurality of second interest points belonging to the second inverse geographic service level according to their locations, and determine a target second interest point from the plurality of second interest points after the clustering process;
[0031] A generating module is used to generate reverse geocoding data of the target area by using the first point of interest and the target second point of interest.
[0032] In a possible implementation, the clustering module is specifically used to:
[0033] Clustering the plurality of second interest points according to their locations to obtain a clustering result, wherein the clustering result includes cluster clusters and / or noise points;
[0034] If the clustering result includes a cluster but does not include a noise point, selecting a representative second interest point from a plurality of second interest points included in the cluster, and determining the representative second interest point as a target second interest point;
[0035] If the clustering result includes a noise point but does not include a clustering cluster, determining the noise point as a target second interest point;
[0036] If the clustering result includes clusters and noise points, a representative second interest point is selected from the plurality of second interest points included in the clusters, and the representative second interest point and the noise point are determined as the target second interest point.
[0037] In a possible implementation, the clustering module is specifically used to:
[0038] Based on the attribute information respectively corresponding to the plurality of second interest points included in the cluster and the weight coefficient corresponding to each attribute information, determine the reverse geography service degree values respectively corresponding to the plurality of second interest points included in the cluster, wherein the reverse geography service degree values are used to measure the friendliness of the reverse geocoding service provided to the user as the reverse geocoding data;
[0039] Based on the inverse geographic service level values respectively corresponding to the plurality of second interest points included in the cluster, a second interest point with the largest inverse geographic service level value is selected from the plurality of second interest points included in the cluster as the representative second interest point.
[0040] In a possible implementation manner, the attribute information includes regional affiliation information, and the clustering module is specifically configured to:
[0041] Based on the regional belonging information respectively corresponding to the plurality of second points of interest, determining the administrative regions to which the plurality of second points of interest respectively belong, and grouping the plurality of second points of interest according to the administrative regions to which they belong, to obtain second points of interest corresponding to different groups;
[0042] For any group of second interest points, a plurality of second interest points in the group are clustered according to their locations to obtain clustering results corresponding to different groups.
[0043] In a possible implementation, the classification module is specifically used for:
[0044] Determining the inverse geographic service degree values corresponding to the plurality of interest points respectively based on the attribute information respectively corresponding to the plurality of interest points and the weight coefficient corresponding to each attribute information;
[0045] Compare the inverse geographic service degree values respectively corresponding to the plurality of interest points with a preset inverse geographic service threshold to obtain comparison results respectively corresponding to the plurality of interest points;
[0046] Based on the comparison results respectively corresponding to the multiple points of interest, the reverse geographic service levels respectively corresponding to the multiple points of interest are determined.
[0047] In a possible implementation, the clustering module is specifically used to:
[0048] A density-based spatial clustering algorithm with noise is used to perform clustering processing on the plurality of second interest points.
[0049] In a third aspect, an embodiment of the present application provides a device for generating reverse geocoding data, including: a memory, a processor;
[0050] The memory stores computer-executable instructions;
[0051] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.
[0052] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.
[0053] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.
[0054] The reverse geocoding data generation method, apparatus, device, medium and program product provided in the embodiments of the present application, by classifying the points of interest in the target area into first points of interest with a higher reverse geography service level and second points of interest with a lower reverse geography service level according to their reverse geography service levels, for multiple second points of interest with a lower reverse geography service level, by clustering the multiple second points of interest according to their locations, representative target second points of interest are screened out, and the first points of interest and the representative target second points of interest are used to generate reverse geocoding data for the target area, that is, some second points of interest with a lower reverse geography service level are retained in the reverse geocoding data, so that when using reverse geocoding technology to search for points of interest near the geographic coordinates of a remote area (usually where the first points of interest do not exist), suitable points of interest can also be obtained, thereby improving the accuracy of the points of interest near the acquired geographic coordinates and improving the service effect of the reverse geocoding service. BRIEF DESCRIPTION OF THE DRAWINGS
[0055] 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.
[0056] Figure 1 A schematic diagram of a scenario for the reverse geocoding data generation method provided in this application;
[0057] Figure 2 Schematic diagram of the reverse geocoding data generation method provided for this application Figure 1 ;
[0058] Figure 3 Schematic diagram of the reverse geocoding data generation method provided for this application Figure 2 ;
[0059] Figure 4 A schematic diagram of the clustering results obtained by clustering processing provided in this application;
[0060] Figure 5 A schematic diagram of clusters and noise points obtained by clustering provided in this application;
[0061] Figure 6 A flowchart of the method for generating reverse geocoding data provided in this application;
[0062] Figure 7 A schematic diagram of the structure of the reverse geocoding data generation device provided in this application;
[0063] Figure 8 A schematic diagram of the structure of the reverse geocoding data generation device provided in this application.
[0064] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION
[0065] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.
[0066] Reverse geocoding services can provide users with accurate and detailed address description information. Reverse geocoding databases usually contain multiple types of data, such as administrative area data, road data, point of interest data, door address data and other reverse geocoding data. These data together constitute the basis of reverse geocoding services.
[0067] The application scenario of the present application is specifically a scenario for generating reverse geocoding data, wherein map data can be processed in a server to generate corresponding reverse geocoding data. In addition, reverse geocoding data can also be generated in a terminal device, which can be a desktop computer, a laptop computer, a tablet computer, a smart phone, etc.
[0068] Figure 1 A schematic diagram of a reverse geocoding data generation method provided in this application, such as Figure 1 As shown, the map data is processed in the terminal device to generate reverse geocoding data.
[0069] Combined with the above scenario, in a related technology, considering the response speed of the reverse geocoding service, it is usually necessary to screen out the specified type of points of interest from the points of interest in the map data, and the specified type of points of interest are points of interest with a higher reverse geocoding service level, and then use the screened points of interest to generate reverse geocoding data. The reverse geocoding data generated by this method is prone to uneven distribution of points of interest, with dense points of interest in the core area and sparse points of interest in the remote area, and the remote area may lack the reverse geocoding data of the remote area due to the lack of the specified type of points of interest, which in turn leads to the point of interest recognition result returned by the reverse geocoding service being inaccurate; in another related technology, a grid-based point of interest selection method is used to select appropriate points of interest from multiple points of interest contained in the map data to generate reverse geocoding data. This method requires grid division and calculation of the relationship between the grid and the points of interest, so the amount of calculation is very large; in another related technology, professional software is used to select points of interest. This method requires a lot of manpower, the time for selecting points of interest is long, and the selection is prone to errors, resulting in low efficiency in generating reverse geocoding data.
[0070] The reverse geocoding data generation method provided by the present application classifies the points of interest in the target area into first points of interest with a higher reverse geography service level and second points of interest with a lower reverse geography service level according to their reverse geography service levels. For multiple second points of interest with a lower reverse geography service level, representative target second points of interest are screened out by clustering the multiple second points of interest according to their locations. The first points of interest and the representative target second points of interest are used to generate reverse geocoding data for the target area. That is to say, some second points of interest with a lower reverse geography service level are retained in the reverse geocoding data, so that when using reverse geocoding technology to search for points of interest near the geographic coordinates of a remote area (usually where the first points of interest do not exist), suitable points of interest can also be obtained, thereby solving the technical problem that the point of interest recognition results returned by the reverse geocoding service are not accurate enough.
[0071] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.
[0072] Figure 2 Schematic diagram of the reverse geocoding data generation method provided for this application Figure 1 ,like Figure 2 As shown, the method includes:
[0073] S201: Acquire multiple points of interest in a target area.
[0074] In an embodiment of the present application, map data of a target area may be obtained, and point of interest data in the map data may be obtained, where the point of interest data includes a plurality of points of interest.
[0075] S202. Determine the reverse geographic service levels corresponding to the multiple points of interest based on the attribute information corresponding to the multiple points of interest respectively, and classify the multiple points of interest into a first point of interest and a second point of interest according to their reverse geographic service levels. The first point of interest corresponds to the first reverse geographic service level, and the second point of interest corresponds to the second reverse geographic service level. The first reverse geographic service level is higher than the second reverse geographic service level.
[0076] The reverse geocoding service level is the service level of reverse geocoding services provided to users as reverse geocoding data. The higher the reverse geocoding service level, the more user-friendly the reverse geocoding service provided is, that is, the point of interest is more likely to be the point of interest that the user expects to return to, lowering the user's usage threshold.
[0077] In an embodiment of the present application, attribute information corresponding to multiple points of interest can be obtained, and based on the attribute information corresponding to the multiple points of interest, the reverse geographic service levels corresponding to the multiple points of interest can be determined, and the multiple points of interest can be classified into a first point of interest and a second point of interest according to their reverse geographic service levels. The first point of interest corresponds to the first reverse geographic service level, and the second point of interest corresponds to the second reverse geographic service level. The first reverse geographic service level is higher than the second reverse geographic service level.
[0078] S203: For a plurality of second points of interest belonging to a second inverse geographic service level, cluster the plurality of second points of interest according to their locations, and determine a target second point of interest from the plurality of second points of interest after the clustering process.
[0079] In an embodiment of the present application, for multiple second points of interest belonging to the second inverse geographic service level, the multiple second points of interest can be clustered according to their locations, and representative second points of interest can be screened out from the multiple second points of interest after clustering, and these representative second points of interest can be used as target second points of interest.
[0080] S204: Generate reverse geocoding data of the target area using the first point of interest and the target second point of interest.
[0081] The reverse geocoding data of the target area is generated by using a first point of interest with a higher reverse geocoding service level and a representative target second point of interest. Specifically, the attribute information of the first point of interest and the attribute information of the target second point of interest can be sent to a database table of a reverse geocoding database for storage, thereby obtaining the reverse geocoding data of the target area. The attribute information can include the ID, name, address, longitude and latitude, type (such as restaurant, hotel, scenic spot, etc.), custom attributes, etc. of the point of interest. When it is necessary to provide reverse geocoding services, suitable points of interest can be found from the database table.
[0082] The reverse geocoding data generation method provided in the embodiment of the present application classifies the points of interest in the target area into first points of interest with a higher reverse geography service level and second points of interest with a lower reverse geography service level according to their reverse geography service levels. For multiple second points of interest with a lower reverse geography service level, representative target second points of interest are screened out by clustering the multiple second points of interest according to their locations. The first points of interest and the representative target second points of interest are used to generate reverse geocoding data for the target area. That is, some second points of interest with a lower reverse geography service level are retained in the reverse geocoding data, so that when using reverse geocoding technology to search for points of interest near the geographic coordinates of a remote area (usually where the first points of interest do not exist), suitable points of interest can also be obtained, thereby improving the accuracy of the points of interest near the acquired geographic coordinates and improving the service effect of the reverse geocoding service.
[0083] Figure 3 Schematic diagram of the reverse geocoding data generation method provided for this application Figure 2 ,like Figure 3 As shown, in this embodiment Figure 2 Based on the embodiment, a method for generating reverse geocoding data is described in detail, and the method includes:
[0084] S301: Acquire multiple points of interest in a target area.
[0085] In the embodiment of the present application, all points of interest in the target area can be obtained.
[0086] S302. Determine the reverse geographic service levels corresponding to the multiple points of interest based on the attribute information corresponding to the multiple points of interest respectively, and classify the multiple points of interest into a first point of interest and a second point of interest according to their reverse geographic service levels. The first point of interest corresponds to the first reverse geographic service level, and the second point of interest corresponds to the second reverse geographic service level. The first reverse geographic service level is higher than the second reverse geographic service level.
[0087] In a possible implementation, based on the attribute information respectively corresponding to the multiple points of interest, determining the reverse geographic service levels respectively corresponding to the multiple points of interest may specifically include:
[0088] Determine the inverse geographic service degree values corresponding to the plurality of interest points based on the attribute information corresponding to the plurality of interest points and the weight coefficient corresponding to each attribute information;
[0089] Compare the inverse geographic service degree values corresponding to the multiple points of interest respectively with the preset inverse geographic service threshold to obtain the comparison results corresponding to the multiple points of interest respectively;
[0090] Based on the comparison results respectively corresponding to the multiple points of interest, the reverse geographic service levels respectively corresponding to the multiple points of interest are determined.
[0091] In this embodiment, the attribute information may include one or more of type, importance, ranking, popularity and whether it is a main point of interest. For a certain point of interest, the reverse geography service level value of the point of interest can be determined based on the attribute information of the point of interest and the weight coefficient corresponding to each attribute information. The reverse geography service level value is used to measure the friendliness of providing reverse geocoding services to users using the point of interest as reverse geocoding data.
[0092] In a possible implementation, based on the attribute information corresponding to the multiple points of interest and the weight coefficient corresponding to each attribute information, determining the inverse geographic service level values corresponding to the multiple points of interest respectively may specifically include:
[0093] Based on the attribute information respectively corresponding to the multiple points of interest, determining scores of the multiple points of interest corresponding to different attribute information;
[0094] Based on the scores of the multiple interest points corresponding to different attribute information and the weight coefficients corresponding to the attribute information, the inverse geographic service degree values corresponding to the multiple interest points are calculated.
[0095] For example, assuming that the score of the type attribute information of a certain point of interest is score1, the score of the importance attribute information is score2, the score of the ranking attribute information is score3, and the score of the heat attribute information is score4, the weight coefficient corresponding to the type attribute information is Q1, the weight coefficient corresponding to the importance attribute information is Q2, the weight coefficient corresponding to the ranking attribute information is Q3, and the weight coefficient corresponding to the heat attribute information is Q4, then the inverse geographic service level value of the point of interest can be obtained as follows:
[0096] T-score=score1×Q1+score2×Q2+score3×Q3+score4×Q4;
[0097] After determining the inverse geographic service degree values corresponding to the plurality of interest points, the inverse geographic service levels corresponding to the plurality of interest points can be determined. Specifically, if the inverse geographic service degree value of a certain interest point is greater than a preset inverse geographic service threshold, the interest point can be determined to be a first interest point with a higher inverse geographic service level. If the inverse geographic service degree value of a certain interest point is not greater than the preset inverse geographic service threshold, the interest point can be determined to be a second interest point with a lower inverse geographic service level. In this embodiment, the interest points are classified by combining various attribute information to determine whether the interest points are the first interest points or the second interest points.
[0098] There are many types of POIs, such as scenic spots, office buildings, schools, squares, museums, hotels, restaurants, and shopping malls. In specific implementation, POIs can be divided into two categories: regional POIs and feature POIs. Regional POIs focus more on the overall attractiveness and functional diversity in a specific area, while feature POIs focus more on specific geographical entities or landmark buildings. In addition, regional POIs may contain multiple feature POIs, while feature POIs usually exist as a single entity.
[0099] As an example, if the type attribute information of the interest point indicates that the interest point is a regional interest point, the score of the interest point in the type attribute information can be determined to be a first score; if the type attribute information of the interest point indicates that the interest point is a ground feature interest point, the score of the interest point in the type attribute information can be determined to be a second score, and the first score is greater than the second score.
[0100] In an embodiment of the present application, by classifying all points of interest in the target area into first points of interest and second points of interest, a first point of interest set and a second point of interest set are obtained, the first point of interest set is a key point of interest set, and the second point of interest set is a non-key point of interest set.
[0101] S303: For a plurality of second interest points belonging to a second inverse geographic service level, cluster the plurality of second interest points according to their locations to obtain a clustering result, where the clustering result includes cluster clusters and / or noise points.
[0102] In a possible implementation, clustering the multiple second interest points according to their locations may specifically include:
[0103] A density-based spatial clustering algorithm with noise is used to cluster the multiple second interest points.
[0104] In this embodiment, a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm can be used to cluster multiple second interest points by specifying a neighborhood radius and a density threshold to obtain cluster clusters and / or noise points.
[0105] Reference Figure 4 As shown, it is a schematic diagram of the clustering result obtained by clustering processing provided by this application, referring to Figure 5 , which is a schematic diagram of clusters and noise points obtained by clustering provided by the present application, wherein the POI cluster is the cluster.
[0106] In a possible implementation, the attribute information includes regional affiliation information, and clustering is performed on the plurality of second interest points according to their locations to obtain a clustering result, which may specifically include:
[0107] Based on the regional belonging information respectively corresponding to the plurality of second points of interest, determining the administrative regions to which the plurality of second points of interest respectively belong, and grouping the plurality of second points of interest according to the administrative regions to which they belong, to obtain second points of interest corresponding to different groups;
[0108] For any group of second interest points, a plurality of second interest points in the group are clustered according to their locations to obtain clustering results corresponding to different groups.
[0109] In this embodiment, multiple second interest points in the second interest point set can be first grouped according to the administrative regions to which they belong. Specifically, the administrative regions to which the multiple second interest points belong can be determined based on the regional affiliation information corresponding to the multiple second interest points. Then, the multiple second interest points can be grouped according to the administrative regions to which they belong, and then each group of second interest points can be clustered to obtain clustering results corresponding to different groups.
[0110] S304: If the clustering result includes a cluster but does not include a noise point, a representative second interest point is selected from the plurality of second interest points included in the cluster, and the representative second interest point is determined as a target second interest point.
[0111] S305: If the clustering result includes a noise point but does not include a cluster, the noise point is determined as a target second interest point.
[0112] S306: If the clustering result includes clusters and noise points, select representative second interest points from the multiple second interest points included in the clusters, and determine the representative second interest points and the noise points as target second interest points.
[0113] In an embodiment of the present application, if the clustering result only contains clusters and does not contain noise points, for each cluster, a representative second interest point is selected from the multiple second interest points contained in the cluster, and the representative second interest point is determined as the target second interest point to obtain the target second interest points corresponding to different clusters.
[0114] If the clustering result only contains noise points but no clustering clusters, all noise points can be directly determined as target second interest points.
[0115] If the clustering result includes both clusters and noise points, representative second interest points are extracted for each cluster, and the representative second interest points and the noise points are determined as target second interest points.
[0116] In a possible implementation, selecting a representative second interest point from a plurality of second interest points included in the cluster may specifically include:
[0117] Based on the attribute information respectively corresponding to the plurality of second interest points included in the cluster and the weight coefficient corresponding to each attribute information, the reverse geography service degree values respectively corresponding to the plurality of second interest points included in the cluster are determined, and the reverse geography service degree values are used to measure the friendliness of the reverse geocoding service provided to the user as the reverse geocoding data;
[0118] Based on the inverse geographic service levels corresponding to the plurality of second interest points included in the cluster, a second interest point with the largest inverse geographic service level value is selected from the plurality of second interest points included in the cluster as a representative second interest point.
[0119] The attribute information includes one or more of type, importance, ranking, popularity, and whether it is a main point of interest.
[0120] In this embodiment, for each cluster, a representative second point of interest may be screened out, wherein for one cluster, only one representative second point of interest may be screened out, or multiple representative second points of interest may be screened out.
[0121] In a possible implementation, if the number of second interest points included in the cluster meets a preset number requirement, no less than a specified number of representative second interest points may be screened.
[0122] S307: Generate reverse geocoding data of the target area using the first point of interest and the target second point of interest.
[0123] The attribute information of the first point of interest and the attribute information of the target second point of interest may be sent to a database table of a reverse geocoding database for storage, thereby obtaining reverse geocoding data of the target area.
[0124] Reference Figure 6 As shown, it is a flowchart of the reverse geocoding data generation method provided by the present application. First, all the points of interest in the target area can be obtained, and then all the points of interest can be classified into first points of interest and second points of interest through attribute information. For the second points of interest, grouping processing is performed according to administrative areas, and for each group of second points of interest, clustering processing is performed separately to obtain cluster clusters and / or noise points, and the target second points of interest are determined from the cluster clusters and / or noise points, and the final reverse geocoding data is generated based on the target second points of interest and the first points of interest.
[0125] The reverse geocoding data generation method provided in the embodiment of the present application classifies the points of interest in the target area into first points of interest with a higher reverse geography service level and second points of interest with a lower reverse geography service level according to their reverse geography service levels. For multiple second points of interest with a lower reverse geography service level, representative target second points of interest are screened out by clustering the multiple second points of interest according to their locations. The first points of interest and the representative target second points of interest are used to generate reverse geocoding data for the target area. That is, some second points of interest with a lower reverse geography service level are retained in the reverse geocoding data, so that when using reverse geocoding technology to search for points of interest near the geographic coordinates of a remote area (usually where the first points of interest do not exist), suitable points of interest can also be obtained, thereby improving the accuracy of the points of interest near the acquired geographic coordinates and improving the service effect of the reverse geocoding service.
[0126] The reverse geocoding data generation method provided in the embodiment of the present application has less computational effort and is more efficient than the grid-based POI selection method; it requires less manpower and is less prone to errors than using professional software to select POIs; and the present application can use map data to automatically generate reverse geocoding data, thereby enabling rapid updating of reverse geocoding data.
[0127] Figure 7 A schematic diagram of the structure of the reverse geocoding data generation device provided in this application, such as Figure 7 As shown, the reverse geocoding data generating device 70 provided in this embodiment includes:
[0128] An acquisition module 701 is used to acquire multiple points of interest in a target area;
[0129] The classification module 702 is used to determine the inverse geographic service levels corresponding to the multiple points of interest based on the attribute information corresponding to the multiple points of interest, and classify the multiple points of interest into a first point of interest and a second point of interest according to their inverse geographic service levels, the first point of interest corresponds to the first inverse geographic service level, the second point of interest corresponds to the second inverse geographic service level, and the first inverse geographic service level is higher than the second inverse geographic service level;
[0130] The clustering module 703 is used to cluster the plurality of second interest points belonging to the second inverse geographic service level according to their locations, and determine a target second interest point from the plurality of second interest points after the clustering process;
[0131] The generating module 704 is used to generate reverse geocoding data of a target area using the first point of interest and the target second point of interest.
[0132] In a possible implementation, the clustering module is specifically used for:
[0133] Clustering the plurality of second interest points according to their locations to obtain a clustering result, where the clustering result includes cluster clusters and / or noise points;
[0134] If the clustering result includes a cluster but does not include a noise point, a representative second interest point is selected from the plurality of second interest points included in the cluster, and the representative second interest point is determined as a target second interest point;
[0135] If the clustering result contains a noise point but does not contain a cluster, the noise point is determined as the second interest point of the target;
[0136] If the clustering result includes clusters and noise points, a representative second interest point is selected from the plurality of second interest points included in the clusters, and the representative second interest point and the noise point are determined as target second interest points.
[0137] In a possible implementation, the clustering module is specifically used for:
[0138] Based on the attribute information respectively corresponding to the plurality of second interest points included in the cluster and the weight coefficient corresponding to each attribute information, the reverse geography service degree values respectively corresponding to the plurality of second interest points included in the cluster are determined, and the reverse geography service degree values are used to measure the friendliness of the reverse geocoding service provided to the user as the reverse geocoding data;
[0139] Based on the inverse geographic service levels corresponding to the plurality of second interest points included in the cluster, a second interest point with the largest inverse geographic service level value is selected from the plurality of second interest points included in the cluster as a representative second interest point.
[0140] In a possible implementation, the attribute information includes regional affiliation information, and the clustering module is specifically used to:
[0141] Based on the regional belonging information respectively corresponding to the plurality of second points of interest, determining the administrative regions to which the plurality of second points of interest respectively belong, and grouping the plurality of second points of interest according to the administrative regions to which they belong, to obtain second points of interest corresponding to different groups;
[0142] For any group of second interest points, a plurality of second interest points in the group are clustered according to their locations to obtain clustering results corresponding to different groups.
[0143] In a possible implementation, the classification module is specifically used for:
[0144] Determine the inverse geographic service degree values corresponding to the plurality of interest points based on the attribute information corresponding to the plurality of interest points and the weight coefficient corresponding to each attribute information;
[0145] Compare the inverse geographic service degree values corresponding to the multiple points of interest respectively with the preset inverse geographic service threshold to obtain the comparison results corresponding to the multiple points of interest respectively;
[0146] Based on the comparison results respectively corresponding to the multiple points of interest, the reverse geographic service levels respectively corresponding to the multiple points of interest are determined.
[0147] In a possible implementation, the clustering module is specifically used for:
[0148] A density-based spatial clustering algorithm with noise is used to cluster the multiple second interest points.
[0149] The reverse geocoding data generation device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be described in detail here.
[0150] Figure 8 This is a schematic diagram of the structure of the reverse geocoding data generation device provided in this application. Figure 8 As shown, the reverse geocoding data generating device 80 provided in this embodiment includes: at least one processor 801 and a memory 802. Optionally, the device 80 also includes a communication component 803. The processor 801, the memory 802 and the communication component 803 are connected via a bus.
[0151] In a specific implementation process, at least one processor 801 executes the computer-executable instructions stored in the memory 802, so that at least one processor 801 executes the above method.
[0152] The specific implementation process of the processor 801 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.
[0153] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.
[0154] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.
[0155] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.
[0156] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.
[0157] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.
[0158] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.
[0159] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.
[0160] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.
[0161] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0162] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
[0163] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.
[0164] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.
[0165] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.
Claims
1. A method for generating reverse geocoding data, characterized in that: include: Get multiple points of interest in the target area; Based on the attribute information respectively corresponding to the multiple points of interest, determine the reverse geographic service levels respectively corresponding to the multiple points of interest, and classify the multiple points of interest into a first point of interest and a second point of interest according to their respective reverse geographic service levels, the first point of interest corresponds to a first reverse geographic service level, the second point of interest corresponds to a second reverse geographic service level, and the first reverse geographic service level is higher than the second reverse geographic service level; For a plurality of second points of interest belonging to a second inverse geographic service level, clustering the plurality of second points of interest according to their locations, and determining a target second point of interest from the plurality of second points of interest after the clustering process; The first point of interest and the target second point of interest are used to generate reverse geocoding data of the target area.
2. The method according to claim 1, characterized in that: The clustering of the plurality of second interest points according to their locations, and determining a target second interest point from the plurality of second interest points after the clustering, comprises: Clustering the plurality of second interest points according to their locations to obtain a clustering result, wherein the clustering result includes cluster clusters and / or noise points; If the clustering result includes a cluster but does not include a noise point, selecting a representative second interest point from a plurality of second interest points included in the cluster, and determining the representative second interest point as a target second interest point; If the clustering result includes a noise point but does not include a clustering cluster, determining the noise point as a target second interest point; If the clustering result includes clusters and noise points, a representative second interest point is selected from the plurality of second interest points included in the clusters, and the representative second interest point and the noise point are determined as the target second interest point.
3. The method according to claim 2, characterized in that The selecting a representative second point of interest from the plurality of second points of interest included in the cluster comprises: Based on the attribute information respectively corresponding to the plurality of second interest points included in the cluster and the weight coefficient corresponding to each attribute information, determine the reverse geography service degree values respectively corresponding to the plurality of second interest points included in the cluster, wherein the reverse geography service degree values are used to measure the friendliness of the reverse geocoding service provided to the user as the reverse geocoding data; Based on the inverse geographic service level values respectively corresponding to the plurality of second interest points included in the cluster, a second interest point with the largest inverse geographic service level value is selected from the plurality of second interest points included in the cluster as the representative second interest point.
4. The method according to claim 2, characterized in that The attribute information includes regional affiliation information, and the clustering process is performed on the plurality of second interest points according to their locations to obtain a clustering result, including: Based on the regional belonging information respectively corresponding to the plurality of second points of interest, determining the administrative regions to which the plurality of second points of interest respectively belong, and grouping the plurality of second points of interest according to the administrative regions to which they belong, to obtain second points of interest corresponding to different groups; For any group of second interest points, a plurality of second interest points in the group are clustered according to their locations to obtain clustering results corresponding to different groups.
5. The method according to any one of claims 1 to 4, characterized in that: The determining, based on the attribute information respectively corresponding to the plurality of interest points, the inverse geographic service levels respectively corresponding to the plurality of interest points comprises: Determining the inverse geographic service degree values corresponding to the plurality of interest points respectively based on the attribute information respectively corresponding to the plurality of interest points and the weight coefficient corresponding to each attribute information; Compare the inverse geographic service degree values respectively corresponding to the plurality of interest points with a preset inverse geographic service threshold to obtain comparison results respectively corresponding to the plurality of interest points; Based on the comparison results respectively corresponding to the multiple points of interest, the reverse geographic service levels respectively corresponding to the multiple points of interest are determined.
6. The method according to any one of claims 1 to 4, characterized in that: The clustering of the plurality of second interest points according to their locations includes: A density-based spatial clustering algorithm with noise is used to perform clustering processing on the plurality of second interest points.
7. A reverse geocoding data generating device, characterized in that: include: An acquisition module, used to acquire multiple points of interest in a target area; a classification module, configured to determine, based on the attribute information respectively corresponding to the plurality of interest points, the inverse geographic service levels respectively corresponding to the plurality of interest points, and classify the plurality of interest points into a first interest point and a second interest point according to the inverse geographic service levels to which they belong, wherein the first interest point corresponds to the first inverse geographic service level, the second interest point corresponds to the second inverse geographic service level, and the first inverse geographic service level is higher than the second inverse geographic service level; A clustering module, configured to cluster the plurality of second interest points belonging to the second inverse geographic service level according to their locations, and determine a target second interest point from the plurality of second interest points after the clustering process; A generating module is used to generate reverse geocoding data of the target area by using the first point of interest and the target second point of interest.
8. A device for generating reverse geocoding data, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.
10. A computer program product, characterized in that The computer program product comprises a computer program, which implements the method according to any one of claims 1 to 6 when executed by a processor.