CN111352964B - Method, device, equipment and storage medium for acquiring interest point information - Google Patents
Method, device, equipment and storage medium for acquiring interest point information Download PDFInfo
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- CN111352964B CN111352964B CN202010082303.8A CN202010082303A CN111352964B CN 111352964 B CN111352964 B CN 111352964B CN 202010082303 A CN202010082303 A CN 202010082303A CN 111352964 B CN111352964 B CN 111352964B
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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 a target track point in a target area; clustering the target track points based on the data of the target track points to obtain one or more clusters, wherein each cluster comprises one or more effective track points; constructing a simulated road corresponding to each cluster, and taking a region meeting the conditions formed by the simulated roads as an interest region in the target region; and acquiring the 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 acquired, which is beneficial to supplementing and perfecting the existing interest point information base and improving the service effect of the service provided based on the interest point information.
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
POI (Point of Interest ) information is indispensable information in an electronic map, and the POI information generally contains information of names, addresses, types, longitude and latitude, and the like, and is used for representing various geographical places encountered in daily life, such as schools, living communities, 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 technology. The technical scheme is as follows:
in one aspect, an embodiment of the present application provides a method for obtaining information about a point of interest, where the method includes:
acquiring data of a target track point in a target area;
clustering the target track points based on the data of the target track points to obtain one or more clusters, wherein each cluster comprises one or more effective track points;
constructing a simulated road corresponding to each cluster, and taking a region which is formed by the simulated roads and meets the condition as an interest region in the target region;
and acquiring the interest point information in the target area based on the target road corresponding to the interest area.
In one possible implementation, the constructing the simulated road corresponding to each cluster includes:
for any cluster, connecting each effective track point in the cluster in sequence;
and constructing a simulated road corresponding to any cluster based on the connecting lines among the effective track points.
In one possible implementation manner, the obtaining, based on the target road corresponding to the region of interest, information of the point of interest in the target region includes:
determining a target road corresponding to the region of interest based on the simulated road forming the region of interest;
and determining the edge information and the center information of the region of interest 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 region of interest as the information of the points of interest in the target region.
In one possible implementation manner, the acquiring the data of the target track point inside the target area includes:
acquiring data of an initial track point and position information of a target area;
and acquiring the data of the target track points in the target area based on the data of the initial track points and the position information of the target area.
In one possible implementation manner, the clustering processing is performed on the target track points based on the data of the target track points to obtain one or more clusters, including:
and responding to the number of the target track points exceeding a number threshold, and carrying out clustering processing on 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 area satisfying the condition is a closed area having an area exceeding an area threshold.
In another aspect, an apparatus for acquiring point of interest information is provided, the apparatus comprising:
the first acquisition module is used for acquiring data of a target track point in the target area;
the clustering module is used for carrying out clustering processing on the target track points based on the data of the target track points to obtain one or more clustering clusters, wherein each clustering cluster comprises one or more effective track points;
the construction module is used for constructing a simulated road corresponding to each cluster, and taking a region which is formed by the simulated roads and meets the condition as an interest region in the target region;
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 one possible implementation manner, the construction module is configured to, for any cluster, connect each valid track point in the any cluster in sequence; and constructing a simulated road corresponding to any cluster based on the connecting lines among the effective track points.
In one possible implementation manner, the second obtaining module is configured to determine, based on a simulated road that forms the region of interest, a target road corresponding to the region of interest; and determining the edge information and the center information of the region of interest 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 region of interest as the information of the points of interest in the target region.
In one 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 points in the target area based on the data of the initial track points and the position information of the target area.
In one 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 to obtain one or more clusters in response to the number of the target track points exceeding a number threshold.
In one possible implementation, the area satisfying the condition is a closed area having an area exceeding an area threshold.
In another aspect, a computer device is provided, where the computer device includes a processor and a memory, where the memory stores at least one piece of program code, and the at least one piece of program code is loaded and executed by the processor to implement any of the methods for obtaining point of interest information described above.
In another aspect, there is provided a computer readable storage medium having at least one program code stored therein, the at least one program code loaded and executed by a processor to implement any of the methods of obtaining point of interest information described above.
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 the 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 acquired, which is beneficial to supplementing and perfecting the existing interest point information base and improving the service effect of the service provided based on the interest point information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an implementation environment of a method for obtaining 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 application;
FIG. 3 is a schematic diagram of target track points before and after clustering according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a cluster obtained according to a DBSCAN clustering algorithm provided by an embodiment of the present application;
FIG. 5 is a schematic diagram illustrating the ordering of each active track point in any cluster according to an embodiment of the present application;
FIG. 6 is a schematic diagram of a simulated roadway according to 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 interest point information in 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 application;
fig. 10 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the application and in the foregoing figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
POI (Point of Interest ) information is indispensable information in an electronic map, and the POI information generally contains information of names, addresses, types, longitude and latitude, and the like, and is used for representing various geographical places encountered in daily life, such as schools, living communities, industrial parks, hospitals, scenic spots, and the like. Currently, some areas of POI information, such as living cells, industrial parks, etc., are deleted from the POI information base. The acquisition of the POI information in the areas is beneficial to supplementing and perfecting the existing POI information base so as to provide more refined service for users 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 this regard, the embodiment of the application provides a method for acquiring interest point information so as to acquire the interest point information in the target area. Referring to fig. 1, a schematic diagram of an implementation environment of a method for acquiring point of interest information according to an embodiment of the present application is shown. The implementation environment may include: a terminal 11 and a server 12.
The terminal 11 may collect data of the motion trail points and then transmit the data of the motion trail points to the server 12. The server 12 may acquire the data of the motion trail point sent by the terminal 11, and acquire the data of the target trail point in the target area according to the data of the motion trail point; the server 12 may further obtain information about points of interest in the target area according to the data about the target track points in the target area. Of course, the terminal 11 may acquire the data of the target track point inside the target area from the server, and then further acquire the point of interest information inside the target area.
In one possible implementation, the terminal 11 may refer to a smart device such as a vehicle-mounted terminal, a mobile phone, a tablet computer, a personal computer, etc. The server 12 may be a server, a server cluster comprising 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.
Those skilled in the art will appreciate that the above-described terminal 11 and server 12 are only examples, and that other terminals or servers that may be present in the present application or in the future are applicable and within the scope of the present application and are incorporated herein by reference.
Based on the implementation environment shown in fig. 1, the embodiment of the application provides a method for acquiring the information of the interest point, and the method 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 a target track point inside a target area is acquired.
The target area refers to an area where the information of the internal interest point is missing in the existing interest point information base, and includes, but is not limited to, an area where a living community is located, an area where an industrial park is located, and the like. In the existing interest point information base, only the interest point information for indicating the position of the target area is generally included, and the interest point information for indicating the garden, the sports square and other interest areas in the target area is not included.
The target track point refers to a track point inside the target area, which may be referred to as a GPS (GlobalPositioning 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 to uniquely identify one target track point.
In one possible implementation, the process of obtaining, by the server, data of a target track point inside the target area includes step 2011 and step 2012:
step 2011: and acquiring the data of the initial track point and the position information of the target area.
In one possible implementation, 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 trail points.
The motion trajectory points refer to trajectory points constituting motion trajectories generated during the motion of a moving object, which may refer to motor vehicles, takeaway riders, pedestrians, and the like. The data of the motion trajectory point may include at least one of position data of the motion trajectory point, a positioning error of the motion trajectory point, a motion speed of the motion trajectory point, and a time stamp of the motion trajectory point. The position data of the motion trail point includes, but is not limited to, longitude values and latitude values of the motion trail point.
The motion trail is generated in the motion process of the moving object, and each motion trail consists of a plurality of motion trail points. The terminal of the moving object can collect the data of the moving track points generated in the moving process of the moving object, and then the collected data of the moving track points are sent to the server. Thereby, the server acquires the data of the movement track points.
The frequency of the terminal for collecting the data of the motion trail points is not limited, and the frequency of the terminal for collecting the data of the motion trail points can be set according to experience and can be freely adjusted according to the type of the moving object. For example, for a motor vehicle, the frequency at which the terminal collects data of the motion trajectory points may be collected every 3 seconds; for takeaway riders, the frequency of the terminal to acquire the data of the motion trail points can be acquired every 5 seconds; for pedestrians, the frequency of the terminal collecting the data of the motion trail points can be that the data are collected 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 motion trail point to the server through the IOT system. Therefore, the server acquires the data of the motion trail 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 a track point database, so that the data of the motion track points can be rapidly extracted from the track point database in the process of subsequently acquiring the data of the initial track points.
In one possible implementation, the data of the motion trail points is encrypted data. In this case, after the server acquires the data of the motion trajectory point, it is necessary to decrypt the data of the motion trajectory point, and then execute the step b according to the decrypted data of the motion trajectory point.
Step b: and filtering the motion track points based on the data of the motion track points, and taking the data of the rest motion track points as the data of the initial track points.
Based on the data of the motion trail points, the motion trail points are filtered, and partial unreliable motion trail points can be removed. In one possible implementation manner, the server filters the motion trail points based on the data of the motion trail points, and the mode includes at least one of the following:
mode one: and eliminating the motion track points with the time stamps not in the reference time range.
This way one occurs in the case where 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 the 01 month 01 day 2020, the initial time stamp is 10:00:00 on the 01 month 01 day 2019, and the reference time range is a time range from 10:00:00 on the 01 month 01 day 2019 to 10:00:00 on the 01 month 01 day 2020.
When the time stamp of the motion trail point is not in the reference time range, the generation time of the motion trail point is early, and the road where the motion trail point is located may have changed. Therefore, the motion trail points with the time stamps not in the reference time range are removed, and partial unreliable motion trail points can be removed.
Mode two: and eliminating the motion track points with the motion speed smaller than the speed threshold value.
The second mode occurs when the data of the motion trail point includes the motion speed of the motion trail point. The motion speed of a motion trajectory point may refer to an instantaneous speed of a moving object at a position where the motion trajectory point is located. The speed threshold may be set empirically or may be freely adjusted according to the type of 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 (meter per second), and if the movement speed corresponding to the movement track point generated by the motor vehicle is less than 1m/s, the movement speed of the motor vehicle is slower, and the movement track point is regarded as an unreliable movement track point and is removed. When the moving object is a pedestrian, the speed threshold value can be set to 20km/h (kilometers per hour), if the moving speed corresponding to the moving track point generated by the pedestrian is smaller than 20km/h, the moving speed of the pedestrian is slower, and the moving track point is taken as an unreliable moving track point and is removed.
Mode three: and removing the motion track points with the positioning errors not smaller than the error threshold value.
The third mode occurs in the case where the data of the motion trajectory point includes a positioning error of the motion trajectory point. The positioning error may refer to a distance error between a positioning position and a true position of the moving object. The error threshold may be set empirically, or may be freely adjusted according to the application scenario, which is not limited in the embodiment of the present application. For example, the error threshold may be set to 8 meters, and when the positioning error of the motion trajectory point is greater than 8 meters, it is indicated that the positioning accuracy of the motion trajectory point is low, and the motion trajectory point is taken as an unreliable motion trajectory point and is removed.
It should be noted that, when the data of the motion trail point includes the time stamp of the motion trail point, the motion speed of the motion trail point and the positioning error of the motion trail point, the motion trail point may be filtered in one or more of the first to third modes, which is not limited in the embodiment of the present application.
After the motion track points are filtered, the rest motion track points are motion track points with higher reliability, and the data of the rest motion track points are used as the data of the initial track points. Thus, the server can acquire data of the initial trajectory point.
The location information of the target area is used to identify the geographic location where the target area is located. In one possible implementation, the manner in which the server obtains the location information of the target area is: the server acquires the existing interest point information corresponding to the target area from the existing interest point information base; and 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 one area includes information in various aspects such as the name of the any one area, the longitude information of the any one area, the latitude information of the any one area, and the detailed description of the any one area. The server can inquire the existing interest point information corresponding to the target area in the existing interest point information base according to the name of the target area; and then taking longitude information and latitude information in the existing interest point information corresponding to the target area as the position information of the target area.
In one possible implementation, the server may call an existing point of interest information base through the interface, and then acquire existing point of interest information corresponding to the target area from the existing point of interest information base.
In one possible implementation manner, the longitude information in the existing interest point information corresponding to the target area includes a lower longitude limit value and an upper longitude limit value; the 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 longitude lower limit value, a longitude upper limit value, a latitude lower limit value, and a latitude upper limit value. A target area can be uniquely determined based on a latitude range composed of a lower longitude limit value and an upper longitude limit value, and a latitude range composed of a lower latitude limit value and an upper latitude limit value.
It should be noted that the number of target areas may be one or more. When the number of the target areas is plural, positional information of each target area is acquired respectively. In one possible implementation manner, after the position information of each target area is acquired, the server may number each target area, and then store the number of the target area and the position information of the target area correspondingly, so as to facilitate subsequent rapid extraction of the position information of the target area.
Step 2012: and acquiring the data of the target track points in the target area based on the data of the initial track points and the position information of the target area.
The initial track point may not be located in the target area, and thus, filtering processing needs to be performed on the initial track point to obtain the target track point in the target area. In one possible implementation, the data of the initial trajectory point includes a longitude value and a latitude value, and the position information of the target area includes a longitude lower limit value, a longitude upper limit value, a latitude lower limit value, and a latitude upper limit value. Based on the data of the initial track points and the position information of the target area, the mode of acquiring the data of the target track points in the target area is as follows: and responding to the longitude value of any initial track point being in 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 being in 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 in the target area.
In one possible implementation, since the accuracy of the obtained point of interest 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 point of interest information. Therefore, after acquiring the data of the target track points inside the target area, it can be detected whether the number of the target track points exceeds the number threshold. Responsive to the number of target trajectory points exceeding the number threshold, performing step 202; and discarding the data of the target track points in the target area in response to the number of the target track points not exceeding the number threshold, and no longer acquiring the interest point information in the target area. By the method, the phenomenon that the accuracy of the information of the interest points 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 an outline of the target area on the 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 area, the larger the number threshold.
When the number of target areas is plural, the data of the target track point in each target area may be acquired. And then the number of each target area and the data of the target track point in each target area can be correspondingly stored so as to be convenient for quick extraction and use. In one possible implementation, the number of each target area and the data of the target track point inside each target area may be correspondingly stored in a List (List) manner.
It should be noted that, in the embodiment of the present application, the number of target areas is taken as one example, and when the number of target areas is plural, the method provided by the embodiment of the present application may be used to obtain the information of the interest point inside each target area.
In step 202, clustering is performed on the target track points based on the data of the target track points, so as to obtain one or more clusters, wherein each cluster comprises one or more effective track points.
The target track points are track points in the target area, the target track points may be located on different roads in the target area, and the target track points possibly 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 possibly do not belong to any cluster, and the target track points which do not belong to any cluster can be used as invalid track points; and taking the target track points in the cluster as effective track points. Each cluster includes one or more active track points therein.
For example, schematic diagrams of target track points before and after the clustering process may be as shown in fig. 3, and after the clustering process, the target track points are clustered into cluster 1, cluster 2, and cluster 3. The target track points in the 3 clusters are effective track points, and the target track points which do not belong to any cluster are ineffective track points.
In one possible implementation, after the server acquires the data of the target track points, it is detected whether the number of the target track points exceeds the number threshold, and this step 202 is performed on the premise that the number of the target track points exceeds the number threshold. That is, in response to the number of 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 clusters.
In one possible implementation manner, based on the data of the target track points, the clustering processing is performed on the target track points, and the manner of obtaining one or more clusters may be: 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 distances between the target track points to obtain a plurality of clusters. Note 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 euclidean distance may be used to represent the distance between the target track points.
In one possible implementation manner, the clustering processing may be performed on the target track points based on the distances between the target track points: and clustering the target track points by using a clustering method based on density based on the distance between the target track points. In general, from the viewpoint of sample density, a density-based clustering method examines connectivity between samples, and continuously expands clusters based on the connectable samples to obtain a final clustering result.
Illustratively, the target track points may be clustered using DBSCAN (Density-Based Spatial Clustering ofApplications with Noise, density-based clustering method with noise). DBSCAN is a density-based spatial clustering algorithm that divides regions of sufficient density into clusters that can be found in noisy spatial databases in arbitrary shapes, which defines clusters as the largest set of density-connected points. The process of clustering by using the DBSCAN may be referred to the description in the related art, and the embodiments of the present application are not described in detail. In the process of clustering target track points by using DBSCAN, two clustering parameters are involved: neighborhood radius and neighborhood target trajectory point minimum number. For any target track point in the cluster obtained after the clustering processing by using the DBSCAN, the number of the target track points included in the circle drawn by taking any target track point as the circle center and taking 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 empirically, and can be freely adjusted according to application scenes, and the embodiment of the application is not limited to the minimum number.
For example, in the case of the target track point distribution shown in fig. 4, two paths corresponding to two arrow connecting lines respectively as 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 one possible implementation, after the clusters are obtained, the clusters may be filtered according to the number of valid track points included in the clusters. When the number of the effective track points included in any cluster does not exceed the reference number, eliminating any cluster; when the number of effective track points included in any cluster exceeds the reference number, the any cluster is reserved. The reference number can be set empirically, or can be freely adjusted according to application scenes, 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 acquiring the interest point information in the target area.
In step 203, a simulated road corresponding to each cluster is constructed, and a region satisfying the condition, which is formed by the simulated road, is set as a region of interest within the target region.
Each cluster may correspond to a road within the target area, and after the clusters are obtained, a simulated road corresponding to each cluster may be constructed. The simulated road is a road simulated inside the target area. It should be noted that, when the server acquires the cluster, the cluster is screened according to the number of the effective track points included in the cluster, where the cluster in this step refers to the reserved cluster, that is, the cluster including the number of the effective track points exceeding 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, connecting each effective track point in the any cluster in turn.
Any cluster comprises one or more effective track points, and each effective track point in any cluster is sequentially connected, so that a connecting line between each effective track point can be obtained.
In one possible implementation, the process of sequentially connecting each effective track point in any cluster may include step a and step B:
step A: and ordering the effective track points based on the data of the effective track points in any cluster.
The data of valid track points includes, but is not limited to, longitude values and latitude values. Implementations of this step a include, but are not limited to, the following two:
mode 1: and sorting the effective track points based on the longitude values of the effective track points in any cluster.
In one possible implementation, the implementation procedure of the mode 1 is: sequencing each effective track point according to the order from small longitude value to large longitude value of each effective track point in any cluster; or, the valid track points in any cluster are ordered in the order of the longitude values of the valid track points from big to small.
Mode 2: and sequencing the effective track points based on the latitude values of the effective track points in any cluster.
In one possible implementation, the implementation procedure of this mode 2 is: sequencing each effective track point according to the order from small to large of the latitude values of each effective track point in any cluster; or, sorting the effective track points according to the order of the latitude values of the effective track points in any cluster from large to small.
Whether the effective track points in any cluster are ordered according to the mode 1 or the mode 2, after the ordering, an ordering result can be obtained, and the ordering result is used for indicating the sequence of the arrangement of the effective track points. In one possible implementation manner, in the process of sorting the effective track points in any cluster, the effective track points can be continuously numbered, and the method can be convenient for quickly knowing the sequence of the arrangement of the effective track points. For example, after each effective track point in any cluster is ordered, the result of the ordering shown in fig. 5 may be obtained, and in fig. 5, each effective track point is continuously numbered from 1 to 16 according to the order of the order.
And (B) step (B): and according to the sequencing result, connecting each effective track point in any cluster in sequence.
The sequencing result is used for indicating the sequence of the arrangement of each effective track point in any cluster, and each effective track point in any cluster is sequentially connected according to the sequence of the arrangement of each track point. For example, as shown in fig. 5, after each effective track point is numbered continuously according to the result of the sorting, each effective track point may be connected in sequence from 1 to 16 in order of the number, so as to obtain a connection line as shown in fig. 5.
Step 2032: based on the connecting lines among the effective track points, a simulated road corresponding to any cluster is constructed.
In one possible implementation manner, based on the connection line between each effective track point, the mode 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 taking a reference value as high, and taking the constructed rectangle as a simulated sub-road corresponding to the any two adjacent effective track points; after obtaining the simulated sub-roads corresponding to all the adjacent effective track points, connecting each simulated sub-road to obtain the simulated road corresponding to any cluster. For example, a simulated road corresponding to any cluster constructed from links between respective effective trajectory points may be as shown in fig. 6.
According to the above steps 2031 and 2032, a simulated road corresponding to each cluster can be constructed. The simulated roads intersect with each other, and can form a plurality of areas. And taking the region meeting the condition in the plurality of regions formed by the simulated road as the region of interest in the target region. The region of interest inside the target region refers to a region inside the target region where the information of the point of interest needs to be acquired. For example, when the target area is an area where a living cell is located, the region of interest inside the target area may refer to an area where a sports square inside the living cell is located. The interest point information of the area where the sports square is located is acquired, so that the method is beneficial to accurately providing relevant information of the sports square in the living community for users.
In one possible implementation, the area satisfying the condition is a closed area having an area exceeding an area threshold. That is, a closed region in which the area of the simulated road exceeds the area threshold is regarded as the region of interest inside the target region. The area threshold may be set empirically, or may be freely adjusted according to the application scenario, which is not limited in the embodiment of the present application. Of course, the area satisfying the condition may also refer to an enclosed area of any area, which is not limited by the embodiment of the present application. For example, when the region constituted by the simulated road is the region shown in fig. 7, the region constituted by the simulated road may be regarded as the region of interest.
In step 204, the information of the points of interest in the target area is obtained based on the target road corresponding to the region of interest.
The target road corresponding to the region of interest refers to a road corresponding to the edge of the region of interest. The target road corresponding to the region of interest may be one or more, which is not limited in the embodiment of the present application. In one possible implementation manner, the process of acquiring the information of the interest point in the target area based on the target road corresponding to the interest area includes step 2041 and step 2042:
step 2041: and determining a target road corresponding to the region of interest based on the simulated roads constituting the region of interest.
The target road corresponding to the region of interest may include a complete simulated road or an incomplete simulated road. According to the simulated roads constituting the region of interest, a target road corresponding to the region of interest can be determined. In one possible implementation manner, the manner of determining the target road corresponding to the region of interest is: and regarding any one of the simulated roads forming the region of interest, taking the road which coincides with the edge of the region of interest in any one of the simulated roads as a target road corresponding to the region of interest.
Step 2042: and determining the edge information and the center information of the region of interest 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 region of interest as the information of the points of interest in the target region.
The edge information of the region of interest is used for identifying a target road corresponding to the region of interest, and the center information of the region of interest is used for identifying a center point of the region of interest. Illustratively, the target road corresponding to the region of interest and the center point of the region of interest may be as shown in fig. 7.
The simulated road is constructed according to the effective track points in the 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 one possible implementation manner, based on the data of the effective track point corresponding to the target road, the manner of determining the edge information of the region of interest 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 point corresponding to the target road comprises, but is not limited to, a longitude value and a latitude value; the width of the target link may refer to the building height of the simulated link.
In one possible implementation manner, based on the data of the effective track point corresponding to the target road, the manner of determining the center information of the region of interest may be: and determining data of a center point according to the data of the effective track point corresponding to the target road, and taking the data of the center point as center 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. The method for determining the data of the center point according to the data of the effective track point corresponding to the target road may be: the average value of the longitude values of the effective track points is taken as the longitude value of the center point, and the average value of the latitude values of the effective track points is taken as the latitude value of the center point. Thereby, data of the center point is obtained.
An edge information and center information corresponding to the edge information may uniquely identify an area of interest. After the edge information and the center information of the region of interest are determined, the road information and the center information are used as the information of the points of interest in the target region. Thereby, the interest point information inside the target area is obtained.
It should be noted that the number of the regions of interest inside the target region may be one or more, which is not limited in the embodiment of the present application. For the case that the number of the interest areas in the target area is one, the interest point information in the target area comprises 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 comprises 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 interest point information in the target area obtained by the method provided by the embodiment of the application is the interest point information predicted by the server, so that the problem of obtaining the interest point 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 inspected in the field.
In summary, the process of acquiring the information of the interest point in 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 the 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 the target track points to obtain one or more clustering clusters; constructing a simulated road corresponding to each cluster; and acquiring the 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, the interest area in the target area is determined based on the data of the target track points in the target area; and then acquiring the 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 acquired, which is beneficial to supplementing and perfecting the existing interest point information base and improving the service effect of the service provided based on the interest point information.
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 the data of the target track points, so as to obtain one or more clusters, where each cluster includes one or more effective track points;
a construction module 903, configured to construct a simulated road corresponding to each cluster, and take a region formed by the simulated roads and meeting the condition as a region of interest inside the target region;
the second obtaining module 904 is configured to obtain, based on a target road corresponding to the region of interest, information of points of interest in the target region.
In one possible implementation manner, the constructing module 903 is configured to, for any cluster, connect each valid track point in any cluster in turn; based on the connecting lines among the effective track points, a simulated road corresponding to any cluster is constructed.
In one possible implementation manner, the second obtaining module 904 is configured to determine a target link corresponding to the region of interest based on the simulated links that constitute the region of interest; and determining the edge information and the center information of the region of interest 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 region of interest as the information of the points of interest in the target region.
In one possible implementation manner, a first obtaining module 901 is configured to obtain data of an initial track point and location information of a target area; and acquiring the data of the target track points in the target area based on the data of the initial track points and the position information of the target area.
In one possible implementation, the clustering module 902 is configured to perform, in response to the number of target track points exceeding the number threshold, clustering on the target track points based on the data of the target track points to obtain one or more clusters.
In one possible implementation, the area satisfying the condition is a closed area having an area exceeding an area threshold.
In the embodiment of the application, the interest area in the target area is determined based on the data of the target track points in the target area; and then acquiring the 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 acquired, which is beneficial to supplementing and perfecting the existing interest point information base and improving the service effect of the service provided based on the interest point information.
It should be noted that, when the apparatus provided in the foregoing embodiment performs the functions thereof, only the division of the foregoing functional modules is used as an example, in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to perform all or part of the functions described above. In addition, the apparatus and the method embodiments provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the apparatus and the method embodiments are detailed in the method embodiments and are not repeated herein.
Fig. 10 is a schematic structural diagram of a server according to an embodiment of the present application, where the server may include one or more processors (CentralProcessing Units, CPU) 1001 and one or more memories 1002, where the one or more memories 1002 store at least one program code, and the at least one program code is loaded and executed by the one or more processors 1001 to implement the method for obtaining point of interest information provided in the foregoing method embodiments. Of course, the server may also have a wired or wireless network interface, a keyboard, an input/output interface, and other components for implementing the functions of the device, which are not described herein.
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 piece of program code is loaded and executed by one or more processors to implement any of the methods of obtaining point of interest information described above.
In an exemplary embodiment, there is also provided a computer-readable storage medium having stored therein at least one program code loaded and executed by a processor of a computer device to implement any of the methods of obtaining point of interest information described above.
Alternatively, the above-mentioned computer readable storage medium may be a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Read-Only optical disk (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.
It should be understood that references herein to "a plurality" are to two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
The foregoing description of the exemplary embodiments of the application is not intended to limit the application to the particular embodiments disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the application.
Claims (10)
1. A method of obtaining point of interest information, the method comprising:
acquiring data of a motion trail point, wherein the data of the motion trail point comprises a time stamp of the motion trail point, a motion speed of the motion trail point, a positioning error of the motion trail point, a longitude value of the motion trail point and a latitude value of the motion trail point;
filtering the data of the motion track points based on the time stamp of the motion track points, the motion speed of the motion track points and the positioning error of the motion track points to obtain data of initial track points, wherein the data of the initial track points comprise the time stamp of the initial track points, the motion speed of the initial track points, the positioning error of the initial track points, the longitude value of the initial track points and the latitude value of the initial track points, the time stamp of the initial track points is in a reference time range, the motion speed of the initial track points is greater than a speed threshold, and the positioning error of the initial track points is less than an error threshold;
Analyzing the existing interest point information corresponding to a target area to obtain the position information of the target area, wherein the position information of the target area comprises a longitude lower limit value, a longitude upper limit value, a latitude lower limit value and a latitude upper limit value corresponding to the target area;
taking the data of an initial track point, of which the longitude value is in a longitude range formed by the longitude lower limit value and the longitude upper limit value and the latitude value is in a latitude range formed by the latitude lower limit value and the latitude upper limit value, as the data of a target track point in the target area;
clustering the target track points based on the data of the target track points to obtain one or more clusters, wherein each cluster comprises one or more effective track points;
for any cluster in the one or more clusters, connecting each effective track point in the any cluster in sequence;
for any two adjacent effective track points of any one of the one or more clusters, taking a connecting line between the any two adjacent effective track points as a median line, taking a reference value as high, constructing a rectangle, and taking the rectangle as a simulated sub-road corresponding to the any two adjacent effective track points;
Connecting each simulated sub-road corresponding to any one of the one or more clusters to obtain a simulated road corresponding to the one or more clusters;
taking a region meeting the conditions, which is formed by the simulated roads corresponding to the one or more clusters, as an interest region inside the target region;
and acquiring interest point information in the target area based on a target road corresponding to the interest area, wherein the interest point information comprises edge information and center information of the interest area.
2. The method according to claim 1, wherein the obtaining the point of interest information in the target area based on the target road corresponding to the region of interest includes:
determining a target road corresponding to the region of interest based on the simulated road forming the region of interest;
and determining the edge information and the center information of the region of interest 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 region of interest as the information of the points of interest in the target region.
3. The method of claim 1, wherein clustering the target track points based on the data of the target track points to obtain one or more clusters comprises:
And responding to the number of the target track points exceeding a number threshold, and carrying out clustering processing on the target track points based on the data of the target track points to obtain the one or more clustering clusters.
4. A method according to any one of claims 1-3, wherein the area meeting the condition is a closed area having an area exceeding an area threshold.
5. An apparatus for obtaining point of interest information, the apparatus comprising:
the first acquisition module is used for acquiring data of the motion trail points, wherein the data of the motion trail points comprise time stamps of the motion trail points, motion speeds of the motion trail points, positioning errors of the motion trail points, longitude values of the motion trail points and latitude values of the motion trail points; filtering the data of the motion track points based on the time stamp of the motion track points, the motion speed of the motion track points and the positioning error of the motion track points to obtain data of initial track points, wherein the data of the initial track points comprise the time stamp of the initial track points, the motion speed of the initial track points, the positioning error of the initial track points, the longitude value of the initial track points and the latitude value of the initial track points, the time stamp of the initial track points is in a reference time range, the motion speed of the initial track points is greater than a speed threshold, and the positioning error of the initial track points is less than an error threshold; analyzing the existing interest point information corresponding to a target area to obtain the position information of the target area, wherein the position information of the target area comprises a longitude lower limit value, a longitude upper limit value, a latitude lower limit value and a latitude upper limit value corresponding to the target area; taking the data of an initial track point, of which the longitude value is in a longitude range formed by the longitude lower limit value and the longitude upper limit value and the latitude value is in a latitude range formed by the latitude lower limit value and the latitude upper limit value, as the data of a target track point in the target area;
The clustering module is used for carrying out clustering processing on the target track points based on the data of the target track points to obtain one or more clustering clusters, wherein each clustering cluster comprises one or more effective track points;
the construction module is used for sequentially connecting each effective track point in any cluster in the one or more clusters; for any two adjacent effective track points of any one of the one or more clusters, taking a connecting line between the any two adjacent effective track points as a median line, taking a reference value as high, constructing a rectangle, and taking the rectangle as a simulated sub-road corresponding to the any two adjacent effective track points; connecting each simulated sub-road corresponding to any one of the one or more clusters to obtain a simulated road corresponding to the one or more clusters; taking a region meeting the conditions, which is formed by the simulated roads corresponding to the one or more clusters, as an interest region inside the target region;
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, wherein the interest point information comprises the edge information and the center information of the interest area.
6. The apparatus of claim 5, wherein the second obtaining module is configured to determine a target link corresponding to the region of interest based on a simulated link that constitutes the region of interest; and determining the edge information and the center information of the region of interest 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 region of interest as the information of the points of interest in the target region.
7. The apparatus of claim 6, wherein the means for clustering, in response to the number of target track points exceeding a number threshold, clusters the target track points based on the data of the target track points to obtain the one or more clusters.
8. The apparatus of any of claims 5-7, wherein the area satisfying the condition is a closed area having an area exceeding an area threshold.
9. A computer device comprising a processor and a memory, wherein the memory has stored therein at least one piece of program code that is loaded and executed by the processor to implement the method of obtaining point of interest information as claimed in any one of claims 1 to 4.
10. A computer readable storage medium having stored therein at least one program code, the at least one program code being loaded and executed by a processor to implement the method of obtaining point of interest information as claimed in any one of claims 1 to 4.
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