CN111352964A - Method, device and equipment for acquiring interest point information and storage medium - Google Patents
Method, device and equipment for acquiring interest point information and storage medium Download PDFInfo
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- CN111352964A CN111352964A CN202010082303.8A CN202010082303A CN111352964A CN 111352964 A CN111352964 A CN 111352964A CN 202010082303 A CN202010082303 A CN 202010082303A CN 111352964 A CN111352964 A CN 111352964A
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Abstract
The application discloses a method, a device, equipment and a storage medium for acquiring interest point information, and belongs to the technical field of computers. The method comprises the following steps: acquiring data of target track points in a target area; based on the data of the target track points, clustering the target track points to obtain one or more clustering clusters, wherein each clustering cluster comprises one or more effective track points; constructing a simulated road corresponding to each cluster, and taking an area satisfying conditions formed by the simulated roads as an interest area in the target area; and acquiring interest point information in the target area based on the target road corresponding to the interest area. Based on the process, the interest point information in the target area can be obtained, the existing interest point information base is favorably supplemented and perfected, and the service effect of the service provided based on the interest point information is favorably improved.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to a method, a device, equipment and a storage medium for acquiring interest point information.
Background
The POI (Point of Interest) information is essential information in an electronic map, and generally includes information such as name, address, type, longitude and latitude, and is used for representing various geographic places encountered in daily life, such as schools, living districts, industrial parks, hospitals, scenic spots, and the like.
Disclosure of Invention
The embodiment of the application provides a method, a device, equipment and a storage medium for acquiring interest point information, which can be used for solving the problems in the related art. The technical scheme is as follows:
in one aspect, an embodiment of the present application provides a method for obtaining point of interest information, where the method includes:
acquiring data of target track points in a target area;
based on the data of the target track points, clustering the target track points to obtain one or more clustering clusters, wherein each clustering cluster comprises one or more effective track points;
constructing a simulated road corresponding to each cluster, and taking an area which is formed by the simulated roads and meets the conditions as an interest area in the target area;
and acquiring interest point information in the target area based on the target road corresponding to the interest area.
In one possible implementation manner, the constructing a simulated road corresponding to each cluster includes:
for any clustering cluster, sequentially connecting each effective track point in the clustering cluster;
and constructing a simulated road corresponding to any clustering cluster based on the connecting lines among the effective track points.
In one possible implementation manner, the obtaining, based on a target road corresponding to the interest region, information of a point of interest inside the target region includes:
determining a target road corresponding to the interest area based on the simulated road forming the interest area;
and determining the edge information and the center information of the interest area based on the data of the effective track points corresponding to the target road, and taking the edge information and the center information of the interest area as the interest point information in the target area.
In a possible implementation manner, the acquiring data of the target track point inside the target region includes:
acquiring data of an initial track point and position information of a target area;
and acquiring the data of the target track point in the target area based on the data of the initial track point and the position information of the target area.
In a possible implementation manner, the clustering the target track point based on the data of the target track point to obtain one or more clustering clusters includes:
and responding to the fact that the number of the target track points exceeds a number threshold value, and clustering the target track points based on the data of the target track points to obtain one or more clustering clusters.
In one possible implementation, the region satisfying the condition is a closed region having an area exceeding an area threshold.
In another aspect, an apparatus for acquiring point of interest information is provided, the apparatus including:
the first acquisition module is used for acquiring data of target track points in a target area;
the clustering module is used for clustering the target track points based on the data of the target track points to obtain one or more clustering clusters, and each clustering cluster comprises one or more effective track points;
the building module is used for building a simulated road corresponding to each cluster, and taking an area which is formed by the simulated roads and meets the conditions as an interest area in the target area;
and the second acquisition module is used for acquiring the interest point information in the target area based on the target road corresponding to the interest area.
In a possible implementation manner, the construction module is configured to, for any one cluster, sequentially connect each effective track point in the any cluster; and constructing a simulated road corresponding to any clustering cluster based on the connecting lines among the effective track points.
In a possible implementation manner, the second obtaining module is configured to determine, based on a simulated road constituting the interest region, a target road corresponding to the interest region; and determining the edge information and the center information of the interest area based on the data of the effective track points corresponding to the target road, and taking the edge information and the center information of the interest area as the interest point information in the target area.
In a possible implementation manner, the first obtaining module is configured to obtain data of an initial track point and position information of a target area; and acquiring the data of the target track point in the target area based on the data of the initial track point and the position information of the target area.
In a possible implementation manner, the clustering module is configured to perform clustering processing on the target track points based on the data of the target track points in response to that the number of the target track points exceeds a number threshold, so as to obtain one or more clustering clusters.
In one possible implementation, the region satisfying the condition is a closed region having an area exceeding an area threshold.
In another aspect, a computer device is provided, which includes a processor and a memory, where at least one program code is stored in the memory, and the at least one program code is loaded and executed by the processor, so as to implement any one of the above methods for obtaining information of a point of interest.
In another aspect, a computer-readable storage medium is provided, in which at least one program code is stored, and the at least one program code is loaded and executed by a processor to implement any one of the above methods for acquiring information of a point of interest.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
determining an interest area in the target area based on the data of the target track points in the target area; and then acquiring interest point information in the target area based on the target road corresponding to the interest area. Based on the process, the interest point information in the target area can be obtained, the existing interest point information base is favorably supplemented and perfected, and the service effect of the service provided based on the interest point information is favorably improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic diagram of an implementation environment of a method for acquiring point of interest information according to an embodiment of the present application;
fig. 2 is a flowchart of a method for obtaining point of interest information according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of target track points before and after clustering processing according to an embodiment of the present application;
fig. 4 is a schematic diagram of obtaining a cluster according to a DBSCAN clustering algorithm provided in an embodiment of the present application;
fig. 5 is a schematic diagram of ordering effective track points in any cluster provided in the embodiment of the present application;
FIG. 6 is a schematic diagram of a simulated road provided by an embodiment of the present application;
FIG. 7 is a schematic diagram of a region of interest provided by an embodiment of the present application;
fig. 8 is a schematic diagram of a process for acquiring information of a point of interest inside a target area according to an embodiment of the present application;
fig. 9 is a schematic diagram of an apparatus for acquiring point of interest information according to an embodiment of the present disclosure;
fig. 10 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
It is noted that the terms "first," "second," and the like (if any) in the description and claims of this application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not 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.
The POI (Point of Interest) information is essential information in an electronic map, and generally includes information such as name, address, type, longitude and latitude, and is used for representing various geographic places encountered in daily life, such as schools, living districts, industrial parks, hospitals, scenic spots, and the like. Currently, the POI information in some areas, for example, the POI information in a living cell, the POI information in an industrial park, etc., are missing from the POI information base. The POI information in the areas is acquired, so that the existing POI information base is supplemented and perfected, and more refined services are provided for the user based on the POI information. Services provided to the user based on the POI information include, but are not limited to, query services, navigation services, and the like.
In view of this, the embodiment of the present application provides a method for acquiring point of interest information, so as to acquire point of interest information inside a target area. Please refer to fig. 1, which illustrates an implementation environment of a method for obtaining point of interest information according to an embodiment of the present application. The implementation environment may include: a terminal 11 and a server 12.
The terminal 11 may collect data of the motion trace points, and then transmit the data of the motion trace points to the server 12. The server 12 may obtain the data of the motion track point sent by the terminal 11, and obtain the data of the target track point in the target area according to the data of the motion track point; the server 12 may further obtain the interest point information in the target area according to the data of the target track point in the target area. Of course, the terminal 11 may also acquire data of a target track point inside the target area from the server, and then further acquire interest point information inside the target area.
In one possible implementation, the terminal 11 may refer to a smart device of a vehicle-mounted terminal, a mobile phone, a tablet computer, a personal computer, or the like. The server 12 may be a server, a server cluster composed of a plurality of servers, or a cloud computing service center. The terminal 11 establishes a communication connection with the server 12 through a wired or wireless network.
It should be understood by those skilled in the art that the above-mentioned terminal 11 and server 12 are only examples, and other existing or future terminals or servers may be suitable for the present application and are included within the scope of the present application and are herein incorporated by reference.
Based on the implementation environment shown in fig. 1, an embodiment of the present application provides a method for obtaining point of interest information, which is applied to a server as an example. As shown in fig. 2, the method provided by the embodiment of the present application may include the following steps:
in step 201, data of target track points inside a target area is acquired.
The target area refers to an area where internal interest point information is missing in an existing interest point information base, and includes but is not limited to an area where a living cell is located, an area where an industrial park is located, and the like. In an existing interest point information base, only interest point information used for indicating a position of a target area is generally included, and interest point information used for indicating interest areas such as gardens, sports squares and the like in the target area is not included.
The target track point refers to a track point located inside the target area, and the track point may refer to a GPS (global positioning System) point. The data of the target track point is used for indicating the position of the target track point. In one possible implementation, the data for the target track point includes, but is not limited to, longitude and latitude values for the target track point. The data of one target track point is used for uniquely identifying one target track point.
In one possible implementation manner, the process of the server obtaining data of the target track point inside the target area includes steps 2011 and 2012:
step 2011: and acquiring data of the initial track point and position information of the target area.
In one possible implementation manner, the process of acquiring the data of the initial track point by the server includes the following steps a and b:
step a: and acquiring data of the motion track points.
The motion track points refer to track points forming a motion track generated by a motion object in a motion process, and the motion object can refer to a motor vehicle, a takeaway rider, a pedestrian and the like. The data of the motion trace point may include at least one of position data of the motion trace point, a positioning error of the motion trace point, a motion speed of the motion trace point, and a time stamp of the motion trace point. The position data of the motion track point includes, but is not limited to, a longitude value and a latitude value of the motion track point.
The moving object can generate moving tracks in the moving process, and each moving track is composed of a plurality of moving track points. The terminal of the moving object can collect the data of the moving track points generated by the moving object in the moving process, and then sends the collected data of the moving track points to the server. Thus, the server acquires data of the motion track points.
The frequency of the data of the motion track points acquired by the terminal is not limited, and the frequency of the data of the motion track points acquired by the terminal can be set according to experience and can also be freely adjusted according to the type of a motion object. For example, for a motor vehicle, the frequency of acquiring the data of the motion track points by the terminal may be acquired every 3 seconds; for the takeaway rider, the frequency of acquiring the data of the motion track points by the terminal can be acquired once every 5 seconds; for pedestrians, the frequency of acquiring the data of the motion track points by the terminal can be once every 10 seconds.
In one possible implementation, the server may run an IOT (Internet of Things) system, and the terminal of the moving object may access the IOT system and then upload the data of the moving track point to the server through the IOT system. Therefore, the server acquires the data of the motion track points through the IOT system.
After the server acquires the data of the motion track points, the data of the motion track points can be stored in the track point database, so that the data of the motion track points can be quickly extracted from the track point database in the subsequent process of acquiring the data of the initial track points.
In one possible implementation, the data of the motion track point is encrypted data. In this case, after the server obtains the data of the motion trace point, the server needs to decrypt the data of the motion trace point, and then executes step b according to the decrypted data of the motion trace point.
Step b: and filtering the motion track points based on the data of the motion track points, and taking the data of the residual motion track points as the data of the initial track points.
Based on the data of the motion track points, the motion track points are filtered, and the motion track points with unreliable parts can be eliminated. In one possible implementation manner, the server filters the motion track points based on the data of the motion track points, where the filtering includes at least one of the following:
the first method is as follows: and eliminating the motion track points of which the time stamps are not in the reference time range.
This occurs when the data of the motion trajectory point includes a time stamp of the motion trajectory point. The reference time range refers to a time range from a start time stamp to a current time stamp, and the start time stamp may be determined according to a reference time interval. The reference time interval may be set empirically or may be freely adjusted according to an application scenario, which is not limited in the embodiment of the present application. For example, the reference time interval may be set to 1 year, and if the current time stamp is 10:00:00 on 01 month 2020, the initial time stamp is 10:00:00 on 01 month 2019, and the reference time range is a time range from 10:00:00 on 01 month 2019 to 10:00:00 on 01 month 2020.
When the time stamp of the motion track point is not in the reference time range, the generation time of the motion track point is earlier, and the road where the motion track point is located may have changed. Therefore, the motion track points of which the time stamps are not in the reference time range are removed, and the partially unreliable motion track points can be removed.
The second method comprises the following steps: and eliminating the motion track points with the motion speed smaller than the speed threshold value.
The second way occurs when the data of the motion track point includes the motion speed of the motion track point. The moving speed of the moving track point may refer to an instantaneous speed of the moving object at a position of the moving track point. The speed threshold may be set empirically, or may be freely adjusted according to the type of the moving object, which is not limited in the embodiment of the present application.
For example, when the moving object is a motor vehicle, the speed threshold may be set to 1m/s (meters per second), and if the moving speed corresponding to the moving track point generated by the motor vehicle is less than 1m/s, it indicates that the moving speed of the motor vehicle is slow, and the moving track point is taken as an unreliable moving track point and removed. When the moving object is a pedestrian, the speed threshold value can be set to be 20km/h (kilometer per hour), if the moving speed corresponding to the moving track point generated by the pedestrian is less than 20km/h, the moving speed of the pedestrian is slow, and the moving track point is taken as an unreliable moving track point and eliminated.
The third method comprises the following steps: and eliminating the motion track points with the positioning errors not smaller than the error threshold.
The third mode occurs under the condition that the data of the motion track points comprise the positioning errors of the motion track points. The positioning error may refer to a distance error between a positioned position of the moving object and a real position. The error threshold may be set empirically, or may be freely adjusted according to an application scenario, which is not limited in this embodiment of the application. Illustratively, the error threshold may be set to 8 meters, and when the positioning error of the motion track point is greater than 8 meters, it is indicated that the positioning accuracy of the motion track point is low, and the motion track point is regarded as an unreliable motion track point and is removed.
It should be noted that, when the data of the motion track point includes the timestamp of the motion track point, the motion speed of the motion track point, and the positioning error of the motion track point, the motion track point may be filtered by one or more of the first to third modes, which is not limited in this embodiment of the present application.
After the motion track points are filtered, the residual motion track points are motion track points with higher reliability, and the data of the residual motion track points are used as the data of the initial track points. Therefore, the server can acquire the data of the initial track point.
The location information of the target area is used to identify the geographic location at which the target area is located. In one possible implementation manner, the manner in which the server obtains the location information of the target area is as follows: the server acquires existing interest point information corresponding to the target area from an existing interest point information base; analyzing the existing interest point information corresponding to the target area to obtain the position information of the target area. In general, the existing point of interest information corresponding to any area includes various information such as a name of the area, longitude information of the area, latitude information of the area, and detailed description of the area. The server can inquire the existing interest point information corresponding to the target area in an existing interest point information base according to the name of the target area; and then longitude information and latitude information in the existing interest point information corresponding to the target area are used as the position information of the target area.
In a possible implementation manner, the server may call an existing interest point information base through the interface, and then obtain existing interest point information corresponding to the target area from the existing interest point information base.
In one possible implementation manner, the longitude information in the existing interest point information corresponding to the target area includes a longitude lower limit value and a longitude upper limit value; latitude information in the existing interest point information corresponding to the target area comprises a latitude lower limit value and a latitude upper limit value. In this case, the position information of the target area includes a lower longitude limit value, an upper longitude limit value, a lower latitude limit value, and an upper latitude limit value. According to the longitude range formed by the lower longitude limit value and the upper longitude limit value and the latitude range formed by the lower latitude limit value and the upper latitude limit value, a target area can be uniquely determined.
It should be noted that the number of target regions may be one or more. When the number of the target areas is multiple, the position information of each target area is respectively acquired. In a possible implementation manner, after the position information of each target area is obtained, the server may number each target area, and then correspondingly store the number of the target area and the position information of the target area, so as to conveniently and quickly extract the position information of the target area subsequently.
Step 2012: and acquiring data of the target track point in the target area based on the data of the initial track point and the position information of the target area.
The position of the initial track point may not be inside the target region, and therefore, the initial track point needs to be filtered to obtain the target track point inside the target region. In one possible implementation, the data of the initial track point includes a longitude value and a latitude value, and the position information of the target area includes a lower longitude value, an upper longitude value, a lower latitude value, and an upper latitude value. Based on the data of the initial track points and the position information of the target area, the method for acquiring the data of the target track points in the target area comprises the following steps: and in response to that the longitude value of any initial track point is within the longitude range formed by the lower longitude limit value and the upper longitude limit value and the latitude value of any initial track point is within the latitude range formed by the lower latitude limit value and the upper latitude limit value, taking the data of any initial track point as the data of the target track point inside the target area.
In one possible implementation, since the accuracy of the obtained interest point information is related to the number of target track points inside the target area, the greater the number of target track points, the higher the accuracy of the obtained interest point information. Therefore, after the data of the target track points in the target area is acquired, whether the number of the target track points exceeds the number threshold value can be detected. In response to the number of target trace points exceeding the number threshold, performing step 202; and in response to the fact that the number of the target track points does not exceed the number threshold, discarding data of the target track points in the target area, and not acquiring interest point information in the target area. By the method, the phenomenon that the accuracy of the interest point information in the target area is low due to the fact that the number of the target track points is too small can be avoided.
The number threshold may be set according to an area of the target area, and the area of the target area may be determined according to a lower longitude limit value, an upper longitude limit value, a lower latitude limit value, and an upper latitude limit value of the target area, or may be determined according to a contour of the target area on a map and a scale of the map, which is not limited in the embodiment of the present application. The larger the area of the target region, the larger the number threshold.
It should be noted that, when the number of the target areas is multiple, data of the target track point inside each target area may be obtained respectively. And then, the number of each target area and the data of the target track point inside each target area can be correspondingly stored, so that the data can be quickly extracted and used. In one possible implementation, the number of each target area and the data of the target track point inside each target area may be stored correspondingly in a List (List).
It should be noted that, in the embodiment of the present application, the number of the target areas is taken as one example for description, and when the number of the target areas is multiple, the point of interest information in each target area may be obtained according to the method provided in the embodiment of the present application.
In step 202, based on the data of the target track point, clustering is performed on the target track point to obtain one or more cluster clusters, where each cluster includes one or more effective track points.
The target track points are track points in the target area, the target track points can be located on different roads in the target area, and the target track points which can be located on the same road can be clustered into the same cluster by clustering the target track points. In the clustering process, some target track points may not belong to any clustering cluster, and the target track points which do not belong to any clustering cluster can be used as invalid track points; and taking the target track points in the clustering cluster as effective track points. Each cluster comprises one or more effective track points.
For example, schematic diagrams of target track points before and after the clustering process can be shown in fig. 3, and after the clustering process, the target track points are clustered into cluster 1, cluster 2, and cluster 3. Target track points in the 3 clustering clusters are effective track points, and target track points which do not belong to any clustering cluster are invalid track points.
In a possible implementation manner, for a case that the server detects whether the number of target track points exceeds the number threshold after acquiring the data of the target track points, the precondition executed in step 202 is that the number of target track points exceeds the number threshold. That is to say, in response to the number of the target track points exceeding the number threshold, the target track points are clustered based on the data of the target track points to obtain one or more cluster clusters.
In a possible implementation manner, based on the data of the target track point, clustering the target track point to obtain one or more clustering clusters may be performed in the following manner: calculating the distance between the target track points based on the data of the target track points; and clustering the target track points based on the distance between the target track points to obtain a plurality of clustering clusters. It should be noted that, in the embodiment of the present application, the manner of representing the distance between the target track points is not limited, and for example, the distance between the target track points may be represented by a euclidean distance.
In a possible implementation manner, the manner of clustering the target track points based on the distance between the target track points may be: and based on the distance between the target track points, clustering the target track points by using a density-based clustering method. In general, the density-based clustering method considers the connectivity among samples from the viewpoint of sample density, and continuously expands a cluster based on connectable samples to obtain a final clustering result.
For example, the target track point may be clustered using DBSCAN (Density-Based clustering of applications with Noise, Density-Based clustering method with Noise). DBSCAN is a density-based spatial clustering algorithm that divides areas with sufficient density into clusters, and can find clusters of arbitrary shape in a spatial database with noise, which defines clusters as the largest set of density-connected points. The process of clustering by using DBSCAN may refer to the introduction in the related art, and the embodiment of the present application is not described again. In the process of clustering target track points by using DBSCAN, two clustering parameters are involved: and the minimum number of neighborhood radius and neighborhood target track points. For any target track point in a clustering cluster obtained after clustering processing is performed by using the DBSCAN, the number of the target track points in a circle drawn by taking the any target track point as the center of the circle and the neighborhood radius as the radius is not less than the minimum number of the neighborhood target track points. The minimum number of the neighborhood radius and the neighborhood target track points can be set according to experience and can also be freely adjusted according to an application scene, and the embodiment of the application does not limit the minimum number of the neighborhood radius and the neighborhood target track points.
For example, under the condition of target track point distribution shown in fig. 4, two paths corresponding to two arrow connecting lines respectively shown in fig. 4 can be obtained according to the DBSCAN clustering algorithm, and the target track points on each path form a cluster.
In a possible implementation manner, after the cluster is obtained, the cluster can be screened according to the number of the effective track points included in the cluster. When the number of the effective track points in any cluster does not exceed the reference number, removing the cluster; and when the number of the effective track points in any cluster exceeds the reference number, keeping the cluster. The reference amount may be set empirically or may be freely adjusted according to an application scenario, which is not limited in the embodiment of the present application. The method is beneficial to reducing the calculated amount and improving the efficiency of obtaining the interest point information in the target area.
In step 203, a simulated road corresponding to each cluster is constructed, and an area satisfying the condition formed by the simulated road is used as an interest area inside the target area.
Each cluster may correspond to a road in the target region, and after the clusters are obtained, a simulated road corresponding to each cluster may be constructed. The simulated road is a road simulated in the target area. It should be noted that, for the case that the server screens the cluster clusters according to the number of the effective track points included in the cluster clusters after obtaining the cluster clusters, the cluster clusters in this step are reserved cluster clusters, that is, cluster clusters including the effective track points whose number exceeds the reference number.
In one possible implementation, the process of constructing the simulated road corresponding to each cluster includes steps 2031 and 2032:
step 2031: and for any cluster, sequentially connecting each effective track point in the cluster.
Any clustering cluster comprises one or more effective track points, and all the effective track points in the clustering cluster are sequentially connected, so that a connecting line between all the effective track points can be obtained.
In a possible implementation manner, the process of sequentially connecting each effective track point in any cluster may include step a and step B:
step A: and sequencing the effective track points based on the data of the effective track points in any clustering cluster.
The data of the valid trajectory points includes, but is not limited to, longitude values and latitude values. The implementation manner of the step a includes, but is not limited to, the following two:
mode 1: and sequencing the effective track points based on the longitude values of the effective track points in any clustering cluster.
In one possible implementation manner, the implementation procedure of the manner 1 is as follows: sequencing each effective track point according to the sequence of the longitude values of each effective track point in any clustering cluster from small to large; or sequencing the effective track points according to the descending order of the longitude values of the effective track points in any clustering cluster.
Mode 2: and sequencing the effective track points based on the latitude values of the effective track points in any clustering cluster.
In one possible implementation manner, the implementation procedure of this manner 2 is: sequencing each effective track point according to the sequence of the latitude values of each effective track point in any clustering cluster from small to large; or sequencing the effective track points according to the descending order of the latitude values of the effective track points in any cluster.
Whether the effective track points in any clustering cluster are sequenced according to the mode 1 or the mode 2, after the effective track points are sequenced, a sequencing result can be obtained, and the sequencing result is used for indicating the sequencing sequence of the effective track points. In a possible implementation mode, in the process of sequencing each effective track point in any clustering cluster, each effective track point can be numbered continuously, and the sequencing sequence of the arrangement of each effective track point can be conveniently and quickly known in the mode. For example, after sorting the effective track points in any cluster, the sorting result shown in fig. 5 can be obtained, and in fig. 5, the effective track points are numbered continuously from 1 to 16 according to the sorting order.
And B: and sequentially connecting each effective track point in any clustering cluster according to the sequencing result.
And the sequencing result is used for indicating the sequencing sequence of each effective track point in any clustering cluster, and each effective track point in any clustering cluster is sequentially connected according to the sequencing sequence of each track point. For example, as shown in fig. 5, after the effective track points are numbered consecutively according to the sorting result, the effective track points may be sequentially connected in the order from 1 to 16 according to the numbering, so as to obtain the connecting line shown in fig. 5.
Step 2032: and constructing a simulated road corresponding to any clustering cluster based on the connecting lines among the effective track points.
In a possible implementation manner, based on the connection line between each effective track point, the manner of constructing the simulated road corresponding to any cluster is as follows: for any two adjacent effective track points, constructing a rectangle by taking a connecting line between the any two adjacent effective track points as a median line and a reference value as a height, and taking the constructed rectangle as a simulated sub-road corresponding to the any two adjacent effective track points; and after the simulated sub-roads corresponding to all the adjacent effective track points are obtained, connecting the simulated sub-roads to obtain the simulated road corresponding to any cluster. For example, a simulated road corresponding to any cluster constructed from the connecting lines between the effective track points can be as shown in fig. 6.
According to the above step 2031 and step 2032, a simulated road corresponding to each cluster can be constructed. The simulated roads are crossed with each other, and a plurality of areas can be formed. And taking an area satisfying the condition in a plurality of areas formed by the simulated roads as an interest area in the target area. The interest area inside the target area refers to an area inside the target area, where the interest point information needs to be acquired. For example, when the target area is an area in which a living cell is located, the interest area inside the target area may refer to an area in which a sports square inside the living cell is located. The interest point information of the area where the sports square is located is obtained, and the method is beneficial to accurately providing the relevant information of the sports square in the living cell for the user.
In one possible implementation, the region satisfying the condition is a closed region having an area exceeding an area threshold. That is, a closed region formed by the simulated road and having an area exceeding an area threshold is set as the region of interest inside the target region. The area threshold may be set empirically, or may be freely adjusted according to an application scenario, which is not limited in the embodiment of the present application. Of course, the region satisfying the condition may also refer to a closed region of any area, which is not limited in the embodiment of the present application. For example, when the area constituted by the pseudo road is the area shown in fig. 7, the area constituted by the pseudo road may be used as the interest area.
In step 204, the interest point information in the target area is obtained based on the target road corresponding to the interest area.
The target road corresponding to the interest area refers to a road corresponding to the edge of the interest area. The target road corresponding to the interest area may be one or more, which is not limited in the embodiment of the present application. In a possible implementation manner, the process of obtaining the interest point information inside the target area based on the target road corresponding to the interest area includes steps 2041 and 2042:
step 2041: and determining a target road corresponding to the interest area based on the simulated road forming the interest area.
The target road corresponding to the interest area may include a complete simulated road or an incomplete simulated road. According to the simulated roads forming the interest area, the target road corresponding to the interest area can be determined. In one possible implementation manner, the manner of determining the target road corresponding to the interest area is as follows: regarding any one of the simulated roads forming the interest area, a road overlapping with the edge of the interest area in the any one of the simulated roads is used as a target road corresponding to the interest area.
Step 2042: and determining the edge information and the center information of the interest area based on the data of the effective track points corresponding to the target road, and taking the edge information and the center information of the interest area as the interest point information in the target area.
The edge information of the interest area is used for identifying a target road corresponding to the interest area, and the center information of the interest area is used for identifying a center point of the interest area. For example, the target road corresponding to the interest region and the center point of the interest region may be as shown in fig. 7.
The simulated road is constructed according to the effective track points in the clustering cluster, and the target road corresponding to the interest area is determined according to the simulated road forming the interest area, so that the target road corresponds to a plurality of effective track points. And determining the data of the effective track points corresponding to the target road according to the data of the effective track points corresponding to the simulated road forming the interest area.
In a possible implementation manner, based on the data of the valid track points corresponding to the target road, the manner of determining the edge information of the interest area may be: and taking the data of the effective track points corresponding to the target road and the width of the target road as the edge information of the interest area. The data of the effective track points corresponding to the target road includes, but is not limited to, a longitude value and a latitude value; the width of the target road may refer to the build height of the simulated road.
In a possible implementation manner, based on the data of the effective track points corresponding to the target road, the manner of determining the center information of the interest area may be: and determining data of the central point according to the data of the effective track points corresponding to the target road, and taking the data of the central point as the central information of the interest area.
In one possible implementation, the data of each valid track point includes a longitude value and a latitude value, and the data of the center point also includes a longitude value and a latitude value. According to the data of the effective track points corresponding to the target road, the data of the central point can be determined in a mode that: and taking the average value of the longitude values of all the effective track points as the longitude value of the central point, and taking the average value of the latitude values of all the effective track points as the latitude value of the central point. Thereby, data of the center point is obtained.
An edge information and a center information corresponding to the edge information can uniquely identify an interest region. After determining the edge information and the center information of the interest area, taking the road information and the center information as the interest point information in the target area. Thereby, the interest point information inside the target area is obtained.
It should be noted that the number of the interest areas inside the target area may be one or more, which is not limited in the embodiments of the present application. For the condition that the number of the interest areas in the target area is one, the interest point information in the target area comprises the interest point information corresponding to the interest area; for the case that the number of the interest areas in the target area is multiple, the interest point information in the target area includes the interest point information corresponding to each interest area.
After the interest point information in the target area is obtained, the interest point information in the target area can be stored in the existing interest point information base so as to supplement and perfect the existing interest point information base. It should be noted that, the point of interest information in the target area obtained by the method provided in the embodiment of the present application is the point of interest information predicted by the server, and the problem of obtaining the point of interest information in the target area can be solved to a certain extent. To detect whether the predicted interest point information is accurate or further improve the interest point information in the target area, the target area can be manually examined in the field.
In summary, the process of acquiring the interest point information inside the target area may be as shown in fig. 8. Acquiring data of an initial track point according to the data of the motion track point, and acquiring position information of a target area from an existing interest point information base; acquiring data of target track points in the target area according to the data of the initial track points and the position information of the target area; clustering target track points to obtain one or more clustering clusters; constructing a simulated road corresponding to each cluster; and acquiring interest point information in the target area according to the target road corresponding to the interest area formed by the simulated road.
In the embodiment of the application, an interest area in a target area is determined based on data of target track points in the target area; and then acquiring interest point information in the target area based on the target road corresponding to the interest area. Based on the process, the interest point information in the target area can be obtained, the existing interest point information base is favorably supplemented and perfected, and the service effect of the service provided based on the interest point information is favorably improved.
Referring to fig. 9, an embodiment of the present application provides an apparatus for acquiring point of interest information, where the apparatus includes:
a first obtaining module 901, configured to obtain data of a target track point inside a target area;
the clustering module 902 is configured to perform clustering processing on the target track points based on data of the target track points to obtain one or more clustering clusters, where each clustering cluster includes one or more effective track points;
a building module 903, configured to build a simulated road corresponding to each cluster, and use an area satisfying a condition formed by the simulated road as an interest area inside the target area;
a second obtaining module 904, configured to obtain, based on a target road corresponding to the interest area, information of the interest point in the target area.
In a possible implementation manner, the constructing module 903 is configured to sequentially connect, for any clustering cluster, each effective track point in any clustering cluster; and constructing a simulated road corresponding to any clustering cluster based on the connecting lines among the effective track points.
In a possible implementation manner, the second obtaining module 904 is configured to determine, based on a simulated road constituting the interest region, a target road corresponding to the interest region; and determining the edge information and the center information of the interest area based on the data of the effective track points corresponding to the target road, and taking the edge information and the center information of the interest area as the interest point information in the target area.
In a possible implementation manner, the first obtaining module 901 is configured to obtain data of an initial track point and position information of a target area; and acquiring data of the target track point in the target area based on the data of the initial track point and the position information of the target area.
In a possible implementation manner, the clustering module 902 is configured to perform clustering processing on the target track points based on the data of the target track points in response to that the number of the target track points exceeds a number threshold, so as to obtain one or more clustering clusters.
In one possible implementation, the region satisfying the condition is a closed region having an area exceeding an area threshold.
In the embodiment of the application, an interest area in a target area is determined based on data of target track points in the target area; and then acquiring interest point information in the target area based on the target road corresponding to the interest area. Based on the process, the interest point information in the target area can be obtained, the existing interest point information base is favorably supplemented and perfected, and the service effect of the service provided based on the interest point information is favorably improved.
It should be noted that, when the apparatus provided in the foregoing embodiment implements the functions thereof, only the division of the functional modules is illustrated, and in practical applications, the functions may be distributed by different functional modules according to needs, that is, the internal structure of the apparatus may be divided into different functional modules to implement all or part of the functions described above. In addition, the apparatus and method embodiments provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments for details, which are not described herein again.
Fig. 10 is a schematic structural diagram of a server according to an embodiment of the present application, where the server may generate a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 1001 and one or more memories 1002, where at least one program code is stored in the one or more memories 1002, and is loaded and executed by the one or more processors 1001 to implement the method for obtaining information of a point of interest provided by the foregoing method embodiments. Of course, the server may also have components such as a wired or wireless network interface, a keyboard, and an input/output interface, so as to perform input/output, and the server may also include other components for implementing the functions of the device, which are not described herein again.
In an exemplary embodiment, a computer device is also provided that includes a processor and a memory having at least one program code stored therein. The at least one program code is loaded into and executed by one or more processors to implement any of the above-described methods for obtaining point of interest information.
In an exemplary embodiment, a computer readable storage medium is further provided, in which at least one program code is stored, and the at least one program code is loaded and executed by a processor of a computer device to implement any of the above methods for obtaining point of interest information.
Alternatively, the computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a Compact Disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.
It should be understood that reference to "a plurality" herein means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
The above description is only exemplary of the present application and should not be taken as limiting the present application, and any modifications, equivalents, improvements and the like that are made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (14)
1. A method for obtaining point of interest information, the method comprising:
acquiring data of target track points in a target area;
based on the data of the target track points, clustering the target track points to obtain one or more clustering clusters, wherein each clustering cluster comprises one or more effective track points;
constructing a simulated road corresponding to each cluster, and taking an area which is formed by the simulated roads and meets the conditions as an interest area in the target area;
and acquiring interest point information in the target area based on the target road corresponding to the interest area.
2. The method of claim 1, wherein constructing the simulated road corresponding to each cluster comprises:
for any clustering cluster, sequentially connecting each effective track point in the clustering cluster;
and constructing a simulated road corresponding to any clustering cluster based on the connecting lines among the effective track points.
3. The method according to claim 1, wherein the obtaining of the interest point information inside the target area based on the target road corresponding to the interest area comprises:
determining a target road corresponding to the interest area based on the simulated road forming the interest area;
and determining the edge information and the center information of the interest area based on the data of the effective track points corresponding to the target road, and taking the edge information and the center information of the interest area as the interest point information in the target area.
4. The method of claim 1, wherein the obtaining data of the target track points inside the target region comprises:
acquiring data of an initial track point and position information of a target area;
and acquiring the data of the target track point in the target area based on the data of the initial track point and the position information of the target area.
5. The method according to claim 1, wherein the clustering the target track point based on the data of the target track point to obtain one or more cluster clusters comprises:
and responding to the fact that the number of the target track points exceeds a number threshold value, and clustering the target track points based on the data of the target track points to obtain one or more clustering clusters.
6. The method according to any one of claims 1 to 5, wherein the region satisfying the condition is an enclosed region having an area exceeding an area threshold.
7. An apparatus for obtaining point of interest information, the apparatus comprising:
the first acquisition module is used for acquiring data of target track points in a target area;
the clustering module is used for clustering the target track points based on the data of the target track points to obtain one or more clustering clusters, and each clustering cluster comprises one or more effective track points;
the building module is used for building a simulated road corresponding to each cluster, and taking an area which is formed by the simulated roads and meets the conditions as an interest area in the target area;
and the second acquisition module is used for acquiring the interest point information in the target area based on the target road corresponding to the interest area.
8. The device according to claim 7, wherein the constructing module is configured to, for any one cluster, sequentially connect each effective track point in the any cluster; and constructing a simulated road corresponding to any clustering cluster based on the connecting lines among the effective track points.
9. The apparatus according to claim 7, wherein the second obtaining module is configured to determine a target road corresponding to the interest area based on a simulated road constituting the interest area; and determining the edge information and the center information of the interest area based on the data of the effective track points corresponding to the target road, and taking the edge information and the center information of the interest area as the interest point information in the target area.
10. The device of claim 7, wherein the first obtaining module is configured to obtain data of the initial track point and position information of the target area; and acquiring the data of the target track point in the target area based on the data of the initial track point and the position information of the target area.
11. The device according to claim 7, wherein the clustering module is configured to perform clustering processing on the target track points based on the data of the target track points in response to that the number of the target track points exceeds a number threshold, so as to obtain one or more clustering clusters.
12. The apparatus of any of claims 7-11, wherein the area satisfying the condition is an enclosed area having an area exceeding an area threshold.
13. A computer device comprising a processor and a memory, wherein at least one program code is stored in the memory, and wherein the at least one program code is loaded into and executed by the processor to implement the method of obtaining point of interest information according to any one of claims 1 to 6.
14. A computer-readable storage medium, having at least one program code stored therein, the at least one program code being loaded and executed by a processor to implement the method of obtaining point of interest information according to any one of claims 1 to 6.
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