CN110555061B - Method and device for determining track similarity - Google Patents
Method and device for determining track similarity Download PDFInfo
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- CN110555061B CN110555061B CN201910851151.0A CN201910851151A CN110555061B CN 110555061 B CN110555061 B CN 110555061B CN 201910851151 A CN201910851151 A CN 201910851151A CN 110555061 B CN110555061 B CN 110555061B
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The application discloses a track similarity determining method, and relates to the field of data mining analysis. The specific implementation scheme is as follows: constructing a first behavior track and a second behavior track in a space-time coordinate system according to position information and time information in the target object behavior data; calculating the minimum editing distance for converting the second behavior track into the first behavior track based on the track points of the first behavior track; and determining the similarity of the first behavior track and the second behavior track according to the minimum editing distance. According to the method and the device, the behavior tracks are constructed in the space-time coordinate system by utilizing the position information and the time information, and the similarity of the two behavior tracks is calculated based on the mode of the minimum editing distance, so that the behavior track similarity of the target object can be more accurately obtained.
Description
Technical Field
The application relates to the field of data processing, in particular to the field of data mining analysis.
Background
In the current target object behavior data research scheme, target object behavior data is generally projected into a two-dimensional plane coordinate system to construct and analyze a target object behavior trajectory. However, the method ignores the influence of the time factor on the behavior track of the target object. Especially, when the target object is at the same position for a long time, if the time factor is not considered, the spatial position of the target object is not changed all the time and is reflected in the coordinate system as only one point. In a research scheme considering time factors, due to the fact that the acquisition time of different behavior data is different, the situation that no corresponding data exists on the same time node may occur, and therefore the generated behavior track cannot be accurately researched for similarity.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining track similarity, so as to solve one or more technical problems in the prior art.
In a first aspect, an embodiment of the present application provides a method for determining a trajectory similarity, including:
constructing a first behavior track and a second behavior track in a space-time coordinate system according to position information and time information in the target object behavior data;
calculating the minimum editing distance for converting the second behavior track into the first behavior track based on the track points of the first behavior track;
and determining the similarity of the first behavior track and the second behavior track according to the minimum editing distance.
In the embodiment, the behavior tracks are constructed in the space-time coordinate system by using the position information and the time information, and the similarity of the two behavior tracks is calculated based on the minimum editing distance, so that the behavior track similarity of the target object can be more accurately determined.
In one embodiment, calculating the minimum edit distance for the second behavior trace to transition to the first behavior trace based on the trace points of the first behavior trace includes:
determining a first target track point on the first behavior track;
generating a second target track point on the second behavior track, wherein the coordinates of the second target track point are the same as those of the first target track point;
calculating a first editing distance for generating a second target track point according to a preset editing distance algorithm;
calculating a second editing distance of a second behavior track before the second target track point converted into a first behavior track before the first target track point by using a recursive solving algorithm;
and calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the first editing distance and the second editing distance.
In this embodiment, the second target trace point is generated on the second behavior trace, so that the problem that the second behavior trace lacks trace points for similarity comparison due to insufficient behavior data of the target object is solved.
In one embodiment, calculating the minimum edit distance for the second behavior trace to transition to the first behavior trace based on the trace points of the first behavior trace includes:
determining a third target track point and a fourth target track point on the first behavior track;
removing redundant track points on the second behavior track, wherein the redundant track points are track points of which the time coordinates are between the time coordinates of the third target track point and the fourth target track point;
calculating a third editing distance for removing the redundant track points according to a preset editing distance algorithm;
calculating a fourth editing distance of the first behavior track before the second behavior track before the redundant track point is converted into the third target track point by using a recursive solving algorithm;
and calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the third editing distance and the fourth editing distance.
In the embodiment, the redundant track points are removed from the second behavior track, so that the problem that the similarity comparison between the first behavior track and the second behavior track is difficult to perform due to the fact that the data amount of the user behavior is inconsistent is solved.
In one embodiment, generating a second target trajectory point on a second behavior trajectory includes:
changing one track point on the second behavior track into a second target track point; or the like, or, alternatively,
and adding a second target track point on the second behavior track.
According to the embodiment, different second track point generation modes can be selected according to different conditions.
In one embodiment, the preset edit distance algorithm for changing one track point on the second behavior track into the second target track point is as follows:
wherein, L (P)1，P2) Preset edit distance, P, representing points of change trajectory1Representing a point of the second line, P2Representing a second target track point, x1Is P1Coordinate in the X axis, y1Is P1Coordinate in the Y axis, x2Is P2Coordinate in the X axis, y2Is P2Coordinates on the Y-axis.
The algorithm of the embodiment can accurately calculate the editing distance of the trace point.
In one embodiment, the preset edit distance algorithm for adding a second target track point to the second behavior track is as follows:
wherein, AL (P)k) Preset edit distance, P, representing incremental track pointskIndicating an increased second target track point, PiRepresenting a track point, P, on the second behavior track that precedes the second target track pointjOne trace point, L (P), on the second behavior trace after the second target trace point is representedi，Pk) Representing points of track PiAnd the track point PkEdit distance between, L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
The algorithm of the embodiment can accurately calculate the edit distance of the increased track points.
In one embodiment, the preset edit distance algorithm for removing the redundant track point on the second behavior track is as follows:
wherein DL (P)k) Indicating a preset edit distance, P, for removing redundant trace pointskRepresenting redundant points of track, PiOn the second behavior trackOne track point, P, preceding a redundant track pointjRepresenting a trace point, L (P), on the second behavior trace after the redundant trace pointi，Pk) Representing points of track PiAnd the track point PkEdit distance between, L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
The algorithm of the embodiment can accurately calculate the editing distance for removing the track points.
In one embodiment, constructing a first behavior trace and a second behavior trace in a spatio-temporal coordinate system according to position information and time information in target object behavior data comprises:
generating an initial coordinate point based on a longitude coordinate axis and a latitude coordinate axis of a space-time coordinate system according to the position information;
arranging the initial coordinate points in time sequence based on the time coordinate axis of the space-time coordinate system according to the time information corresponding to the position information to form a plurality of track points;
and constructing a first behavior track and a second behavior track based on the plurality of track points.
In the embodiment, the behavior track containing the time characteristics is constructed in the space-time coordinate system, so that the constructed first behavior track and the second behavior track have higher similarity comparison value.
In one embodiment, before generating the initial coordinate point based on the longitude coordinate axis and the latitude coordinate axis of the spatio-temporal coordinate system according to each position information, the method further includes:
unifying the measurement units of the position information into longitude and latitude units;
and unifying the measurement units of the time information.
According to the embodiment, by unifying the measurement units, the calculation error of the edit distance caused by the inconsistency of the measurement units is solved, and meanwhile, the complexity of constructing the behavior track and calculating the edit distance is reduced.
In a second aspect, an embodiment of the present application provides a trajectory similarity determining apparatus, including:
the building module is used for building a first behavior track and a second behavior track in a space-time coordinate system according to the position information and the time information in the target object behavior data;
the calculation module is used for calculating the minimum editing distance for converting the second behavior track into the first behavior track based on each track point of the first behavior track;
and the determining module is used for determining the similarity between the first behavior track and the second behavior track according to the minimum editing distance.
In one embodiment, the computing module comprises:
the first determining submodule is used for determining a first target track point on the first behavior track;
the first generation submodule is used for generating a second target track point on the second behavior track, and the coordinates of the second target track point are the same as those of the first target track point;
the first calculation submodule is used for calculating and generating a first editing distance of the second target track point according to a preset editing distance algorithm;
the second calculation submodule is used for calculating a second editing distance of a second behavior track before the second target track point is converted into a first behavior track before the first target track point by using a recursive solving algorithm;
and the third calculation submodule is used for calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the first editing distance and the second editing distance.
In one embodiment, the computing module comprises:
the second determining submodule is used for determining a third target track point and a fourth target track point on the first behavior track;
the removing submodule is used for removing redundant track points on the second behavior track, and the redundant track points are track points with time coordinates between the time coordinates of the third target track point and the time coordinates of the fourth target track point;
the fourth calculation submodule is used for calculating a third editing distance for removing the redundant track points according to a preset editing distance algorithm;
the fifth calculation submodule is used for calculating a fourth editing distance of the first behavior track before the second behavior track before the redundant track point is converted into the third target track point by using a recursive solving algorithm;
and the sixth calculating submodule is used for calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the third editing distance and the fourth editing distance.
In one embodiment, the first generation submodule includes:
the generating unit is used for changing one track point on the second behavior track into a second target track point; or, adding a second target track point to the second behavior track.
In one embodiment, the building block comprises:
the second generation submodule is used for generating an initial coordinate point based on a longitude coordinate axis and a latitude coordinate axis of the space-time coordinate system according to the position information;
the forming submodule is used for arranging each initial coordinate point according to the time information corresponding to each position information and the time coordinate axis of the space-time coordinate system in time sequence to form a plurality of track points;
and the constructing submodule is used for constructing the first behavior track and the second behavior track based on the plurality of track points.
In a third aspect, an embodiment of the present application provides an electronic device, where functions of the electronic device may be implemented by hardware, or may be implemented by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described functions.
In one possible design, the electronic device includes a processor and a memory, the memory is used for storing a program for supporting the electronic device to execute the trajectory similarity determination method, and the processor is configured to execute the program stored in the memory. The electronic device may also include a communication interface for communicating with other devices or a communication network.
In a fourth aspect, embodiments of the present application provide a non-transitory computer-readable storage medium storing computer instructions for an electronic device and computer software instructions for the electronic device, which includes a program for performing the above-mentioned trajectory similarity determination.
One embodiment in the above application has the following advantages or benefits: according to the method and the device, the technical means that the behavior tracks are constructed in the space-time coordinate system by utilizing the position information and the time information and the similarity of the two behavior tracks is calculated based on the minimum editing distance are adopted, so that the technical problem that the time factor is ignored when the behavior tracks are constructed and analyzed in the two-dimensional plane coordinate system is solved, and the technical effect of more accurately obtaining the behavior track similarity of the target object is achieved.
Other effects of the above-described alternative will be described below with reference to specific embodiments.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1 is a schematic flowchart of a trajectory similarity determination method according to a first embodiment of the present application;
fig. 2 is a flowchart illustrating step S100 of a trajectory similarity determination method according to a first embodiment of the present application;
FIG. 3 is a schematic diagram of constructing behavior trajectories in a spatiotemporal coordinate system according to a first embodiment of the present application;
fig. 4 is a flowchart illustrating a step S100 of another trajectory similarity determining method according to the first embodiment of the present application;
fig. 5 is a flowchart illustrating step S200 of a trajectory similarity determination method according to a first embodiment of the present application;
fig. 6 is a flowchart illustrating a step S200 of another trajectory similarity determining method according to the first embodiment of the present application;
FIG. 7 is a block flow diagram of a trajectory similarity determination method according to a first embodiment of the present application;
FIG. 8 is a schematic diagram of a trajectory similarity determination apparatus according to a second embodiment of the present application;
FIG. 9 is a schematic diagram of a calculation module of a trajectory similarity determination apparatus according to a second embodiment of the present application;
FIG. 10 is a schematic diagram of a computing module of another trajectory similarity determination apparatus according to a second embodiment of the present application;
fig. 11 is a schematic diagram of a first generation submodule of a trajectory similarity determination apparatus according to a second embodiment of the present application;
FIG. 12 is a schematic diagram of a building block of a trajectory similarity determination apparatus according to a second embodiment of the present application;
fig. 13 is a block diagram of an electronic device for implementing a trajectory similarity determination method according to an embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
According to a first embodiment of the present application, there is provided a method for determining a track similarity, as shown in fig. 1, the method including:
s100: and constructing a first behavior track and a second behavior track in a space-time coordinate system according to the position information and the time information in the target object behavior data.
The target object behavior data may include behavior trace information left by the target object in online or offline activities. For example, the behavior of the target object collected by a road gate, a camera, a base station, etc. For another example, the target object records the behavior of the target object by operating the terminal.
The target object may be a person, a vehicle, or the like.
The location information may include location information, location coordinates, GPS information, etc. of the target object that is behaving at different times. The time information may include a time at which the target object produces the behavior. And the time information is associated with location information, each having corresponding time information.
The space-time coordinate system is at least a three-dimensional space-time coordinate system, and the specifically adopted coordinate system can be selected according to requirements.
The first behavior trace can be constructed based on data of the same behavior data source of the target object or constructed based on data of a plurality of different behavior data sources. The second behavior trace is the same and will not be described again. When constructing the first behavior trace and the second behavior trace, the behavior data of the target object utilized by the two traces may be both the data collected in the same time range. Or only part of the behavior data may be acquired within the same time range. Wherein, the size of the time range can be selected according to the requirement. For example, the behavior data of the same time, the same day, or the same month and year may be used.
In one example, the first behavior trace and the second behavior trace are both constructed fusing online and offline activity behaviors of the target object. Therefore, the behavior track of the target object can be reflected more comprehensively on the basis of two dimensions of time and space.
S200: and calculating the minimum editing distance for converting the second behavior track into the first behavior track based on the track points of the first behavior track. The minimum edit distance can be understood as the minimum operating cost required to completely convert the second behavior trace into the first behavior trace.
S300: and determining the similarity of the first behavior track and the second behavior track according to the minimum editing distance.
In the embodiment, the behavior tracks are constructed in the space-time coordinate system by using the position information and the time information, and the similarity of the two behavior tracks is calculated based on the minimum editing distance, so that the behavior track similarity of the target object can be more accurately determined.
In one embodiment, as shown in fig. 2, constructing a first behavior trace and a second behavior trace in a spatio-temporal coordinate system according to position information and time information in target object behavior data includes:
s110: and generating an initial coordinate point based on a longitude coordinate axis and a latitude coordinate axis of the space-time coordinate system according to the position information.
S120: and arranging the initial coordinate points in time sequence based on the time coordinate axis of the space-time coordinate system according to the time information corresponding to the position information to form a plurality of track points.
S130: and constructing a first behavior track and a second behavior track based on the plurality of track points.
In one example, the trajectory points required to construct the first behavior trace and the trajectory points required to construct the second behavior trace may be selected as desired. The first behavior trace and the second behavior trace may include the same trace points.
In the embodiment, the behavior track containing the time characteristics is constructed in the space-time coordinate system, so that the constructed first behavior track and the second behavior track have higher similarity comparison value.
In one example of an application, as shown in FIG. 3, the spatiotemporal coordinate system includes an X-axis representing longitude, a Y-axis representing latitude, and a Z-axis representing time. Generating a series of coordinate points P in a space-time coordinate system according to the position information and the time information in the target object behavior data1(x1，y1，z1)、P2(x2，y2，z2)、P3(x3，y3，z3)、P4(x4，y4，z4)、Q1(x5，y5，z5)、Q2(x6，y6，z6)、Q3(x7，y7，z7)、Q4(x8，y8，z8). Wherein, P1、P2、P3、P4A first behavior trace, Q, is constructed1、Q2、Q3、Q4A second behavior trace is constructed. Every two track points are connected through a directed vector, and the direction is directedThe quantity represents the time-position relationship between two trace points.
If the position of the target object changes, the position information is different, and the track points generated in the space-time coordinate system are also different. If the position of the target object does not change, but the time is continuous, even if the projection of each track point generated according to the position information on the plane constructed by the XY axes is one point, the projection can still be embodied as different track points (a plurality of track points parallel to the Z axis) on the Z axis. Therefore, even if the position of the target object is not changed, the space-time coordinate system constructed by the method can well show the behavior of the target object.
In one example, the coordinate axis units of the spatio-temporal coordinate system can be selectively adjusted according to needs, and are not limited to longitude and latitude coordinate axes.
In one embodiment, as shown in fig. 4, before generating the initial coordinate point based on the longitude coordinate axis and the latitude coordinate axis of the spatio-temporal coordinate system according to each position information, the method further includes:
s140: and unifying the measurement units of the position information into longitude and latitude units.
S150: and unifying the measurement units of the time information.
According to the embodiment, the complexity of constructing the behavior track and calculating the editing distance is reduced by unifying the measurement units.
In one embodiment, as shown in fig. 5, calculating the minimum edit distance for the second behavior trace to transition to the first behavior trace based on the trace points of the first behavior trace includes:
s201: a first target trajectory point is determined on the first behavior trajectory. The first target trajectory point may be any point on the first behavior trajectory.
S202: and generating a second target track point on the second behavior track, wherein the coordinates of the second target track point are the same as those of the first target track point. It can be understood that the first target track point is generated on the second behavior track.
S203: and calculating a first editing distance for generating a second target track point on the second behavior track according to a preset editing distance algorithm. The preset edit distance algorithm may be different according to different ways of generating the second target track point.
S204: and calculating a second editing distance of the second behavior track before the second target track point converted into the first behavior track before the first target track point by using a recursive solving algorithm.
S205: and calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the first editing distance and the second editing distance.
In this embodiment, the second target trace point is generated on the second behavior trace, so that the problem that the second behavior trace lacks trace points for similarity comparison due to insufficient behavior data of the target object is solved.
In an example, the track points on the second behavior track that are located before the second target track point may also be calculated by the above steps. Each trace point on the second behavior trace may be considered a second target trace point.
In one example, the first behavior trace includes m trace points and the second behavior trace includes n trace points. When the track point m on the first behavior track is used as a first target track point, a track point m is generated on the second behavior track (the track point n on the second behavior track is changed into the track point m), then the editing distance for changing the track point n into the track point m is calculated, and the editing distance for changing the second behavior track before the track point n into the first behavior track before the point m is calculated.
Calculating the editing distance of the second behavior track before the track point n to be converted into the first behavior track before the point m, wherein the method comprises the following steps: taking m-1 on the first behavior track as a first target track point, adding a track point m-1 on a second behavior track before the track point n, then calculating the editing distance of adding a track point m-1 on the second behavior track before the track point n, and calculating the editing distance of converting the second behavior track before the track point m-1 into the first behavior track before the m-1 point.
And sequentially calculating track points on the second behavior track from back to front in a time sequence by using a recursive solving mode until the conversion from the second behavior track to the first behavior track is completed.
In one example, a second edit distance for the second behavior trace to transition to the first behavior trace may also be calculated using a dynamic programming solution.
In one embodiment, generating a second target trajectory point on a second behavior trajectory includes:
and changing one track point on the second behavior track into a second target track point. Or the like, or, alternatively,
and adding a second target track point on the second behavior track.
According to the embodiment, different second track point generation modes can be selected according to different conditions.
In one example, the edit distance between any two trace points in the present application can be calculated using the edit distance formula described below.
Wherein, L (P)1，P2) Indicating the edit distance, P, of two track points1Representing points of track, P2Representing points of track, x1Is P1Position coordinate on X axis, y1Is P1Position coordinate in the Y axis, x2Is P2Position coordinate on X axis, y2Is P2Position coordinate in the Y axis, z1Is P1Time coordinate in Z axis, Z2Is P2In the time coordinate of the Z-axis, k represents a time threshold.
When P is present1And P2When the time difference between the two is less than the time threshold k, the two can pass
And calculating the editing distance.
When P is present1And P2When the time difference between the two tracks is greater than a time threshold k, the two tracks are consideredThe edit distance between the waypoints is infinite.
The time threshold k may be adjusted. When the trace points on the behavior trace are sparse, the k value can be increased appropriately. When the trace points on the behavior trace are denser, the k value can be reduced appropriately. So that the edit distance formula between two trace points can be adapted to different action traces.
In one embodiment, the preset edit distance algorithm for changing one track point on the second behavior track into the second target track point is as follows:
wherein, L (P)1，P2) Preset edit distance, P, representing points of change trajectory1Representing a point of the second line, P2Representing a second target track point, x1Is P1Coordinate in the X axis, y1Is P1Coordinate in the Y axis, x2Is P2Coordinate in the X axis, y2Is P2Coordinates on the Y-axis. When P is present1And P2The time attribute between two points can be erased when the time difference between the two points is less than the time threshold k, and the distance between the two points is equal to the Euclidean distance in the plane coordinate system formed by the X, Y axes, so that the time attribute can be passed through
And calculating the editing distance. When P is present1And P2When the time difference between the two track points is larger than the time threshold k, the edit distance between the two track points is considered to be infinite.
The algorithm of the embodiment can accurately calculate the editing distance of the trace point.
In one embodiment, the preset edit distance algorithm for adding a second target track point to the second behavior track is as follows:
wherein, AL (P)k) Preset edit distance, P, representing incremental track pointskIndicating an increased second target track point, PiRepresenting a track point, P, on the second behavior track that precedes the second target track pointjA trace point on the second behavior trace that is located after the second target trace point is represented. N denotes the last trace point on the second behavior trace. L (P)i，Pk) Representing points of track PiAnd the track point PkThe edit distance between. L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
The algorithm of the embodiment can accurately calculate the edit distance of the increased track points.
In one embodiment, as shown in fig. 6, calculating the minimum edit distance for the second behavior trace to transition to the first behavior trace based on the trace points of the first behavior trace includes:
s206: and determining a third target track point and a fourth target track point on the first behavior track. The third target track point and the fourth target track point may be any two track points on the first behavior track.
S207: and removing redundant track points on the second behavior track, wherein the redundant track points are track points of which the time coordinates are between the time coordinates of the third target track point and the fourth target track point.
In one example, when there are 8 trace points on the first behavior trace and 9 trace points on the second behavior trace, the redundant trace points on the second behavior trace can be removed.
S208: and calculating a third editing distance for removing the redundant track points according to a preset editing distance algorithm.
S209: and calculating a fourth editing distance of the first behavior track before the second behavior track before the redundant track point is converted into the third target track point by using a recursive solving algorithm.
S210: and calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the third editing distance and the fourth editing distance.
In the embodiment, the redundant track points are removed from the second behavior track, so that the problem that the similarity comparison between the first behavior track and the second behavior track is difficult to perform due to the fact that the data amount of the user behavior is inconsistent is solved.
In one embodiment, the preset edit distance algorithm for removing the redundant track point on the second behavior track is as follows:
wherein DL (P)k) Indicating a preset edit distance, P, for removing redundant trace pointskRepresenting redundant points of track, PiRepresenting a trace point, P, preceding the redundant trace point on the second behavior tracejRepresenting a trace point on the second behavior trace that follows the redundant trace point. L (P)i，Pk) Representing points of track PiAnd the track point PkThe edit distance between. L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
The algorithm of the embodiment can accurately calculate the editing distance for removing the track points.
In one example, the second behavior trace may calculate the edit distance from the second behavior trace to the first behavior trace by adding trace points, deleting trace points, and changing trace points, respectively. Different transformation modes of each track point can obtain different editing distances, and the transformation of each track point can generate different degrees of influence on the transformation modes of other track points, so that the editing distances of other track points are changed. Therefore, in order to accurately obtain the minimum editing distance for converting the second behavior track into the first behavior track, the editing distance can be calculated by respectively adopting the three ways for each track point.
In one example, the minimum edit distance for the second behavior trace to transition to the first behavior trace is calculated according to the following formula:
wherein, E (P)a，Qb) Indicating cut-off to trace point PaFirst action track and cut-off to track point QbThe edit distance between the second behavior trace. AL (P)a) Indicating increasing of the trace point Pa。AL(Qb) Indicating increasing of trace point Qb。E(Pa-1，Qb-1) Indicating cut-off to trace point Pa-1First action track and cut-off to track point Qb-1The edit distance between the second behavior trace. E (P)a-1，Qb) Indicating cut-off to trace point Pa-1First action track and cut-off to track point QbThe edit distance between the second behavior trace. E (P)a，Qb-1) Indicating cut-off to trace point PaFirst action track and cut-off to track point Qb-1The edit distance between the second behavior trace. L (P)a，Qb) Representing points of track PaTo the track point QbThe minimum edit distance. a represents the a track point of the first behavior track, b represents the b track point of the second behavior track, m represents the last track point of the first behavior track, and n represents the last track point of the second behavior track.
E(Pa，Qb)＝E(Pa-1，Qb-1) The meaning of (A) is: point of track PaAnd QbAnd (4) overlapping, wherein the increment of the two action tracks is 0 at the moment, so that only the cutoff track point P needs to be calculateda-1First action track and cut-off to track point Qb-1The edit distance between the second behavior trace.
E(Pa，Qb)＝E(Pa-1，Qb-1)+L(Pa，Qb) The meaning of (A) is: calculating the tracing point PaTo the track point QbMinimum edit distance of, and cut-off to, the track point Pa-1First action track and cut-off to track point Qb-1The minimum edit distance between the second behavior trace.
E(Pa，Qb)＝E(Pa-1，Qb)+AL(Pa) The meaning of (A) is: calculating and adding track points P on the second behavior trackaEdit distance of, and cut to, track point Pa-1First action track and cut-off to track point QbThe minimum edit distance between the second behavior trace.
E(Pa，Qb)＝E(Pa，Qb-1)+AL(Qb) The meaning of (A) is: calculating and adding track points Q on the first behavior trackbEdit distance of, and cut to, track point PaFirst action track and cut-off to track point Qb-1The edit distance between the second behavior trace.
Through the recursion algorithm, the similarity of the two behavior tracks can be accurately calculated by recursing the track points.
When the similarity of two action tracks is compared, the problems of track point loss, multi-record track points and error record of track points in target object action data can be solved by means of track point adding, track point deleting and track point changing.
In one example, as shown in fig. 7, the method for determining similarity of trajectories of the present application includes:
and (3) track information coordinating process: and generating an initial coordinate point in a longitude and latitude coordinate system by cavitation of the position information in the track information based on the on-line track information, the off-line track information and other track information of the target object. And then, time information is utilized to carry out time-space serialization on each initial coordinate point to generate a three-dimensional space track point in a time-space coordinate system.
Spatio-temporal trajectory (behavior trajectory) definition process: and defining the editing distance between any two track points, and defining the editing distance for adding the track points, deleting the track points and changing the track points.
Study similarity procedure: and calculating the similarity of the space-time trajectory by using a recursive algorithm in a way of adding trajectory points, deleting trajectory points and changing trajectory points.
According to a second embodiment of the present application, there is provided a trajectory similarity determination apparatus 100, as shown in fig. 8, including:
and the constructing module 10 is configured to construct a first behavior trajectory and a second behavior trajectory in a space-time coordinate system according to the position information and the time information in the target object behavior data.
And the calculating module 20 is configured to calculate a minimum editing distance for converting the second behavior track into the first behavior track based on the track points of the first behavior track.
And the determining module 30 is configured to determine a similarity between the first behavior trace and the second behavior trace according to the minimum editing distance.
In one embodiment, as shown in fig. 9, the calculation module 20 includes:
a first determining submodule 201, configured to determine a first target track point on the first behavior track.
And the first generating sub-module 202 is configured to generate a second target track point on the second behavior track, where the second target track point has the same coordinate as the first target track point.
The first calculating submodule 203 is configured to calculate a first edit distance for generating a second target track point according to a preset edit distance algorithm.
The second calculating sub-module 204 is configured to calculate, by using a recursive solution algorithm, a second edit distance at which the second behavior trajectory before the second target trajectory point is converted into the first behavior trajectory before the first target trajectory point.
And the third calculation submodule 205 is configured to calculate a minimum edit distance for converting the second behavior trace into the first behavior trace according to the first edit distance and the second edit distance.
In one embodiment, as shown in fig. 10, the calculation module 20 includes:
a second determining sub-module 206 for determining a third target track point and a fourth target track point on the first behavior trace.
And the removing submodule 207 is used for removing redundant track points on the second behavior track, wherein the redundant track points are track points of which the time coordinates are between the time coordinates of the third target track point and the fourth target track point.
And the fourth calculating submodule 208 is configured to calculate a third edit distance for removing the redundant track point according to a preset edit distance algorithm.
And the fifth calculating submodule 209 is configured to calculate, by using a recursive solution algorithm, a fourth editing distance of the second behavior trajectory before the redundant trajectory point is converted into the first behavior trajectory before the third target trajectory point.
And the sixth calculating sub-module 210 is configured to calculate a minimum editing distance for converting the second behavior trace into the first behavior trace according to the third editing distance and the fourth editing distance.
In one embodiment, as shown in FIG. 11, the first generation submodule 202 includes:
the generating unit 2021 is configured to change one track point on the second behavior track into a second target track point. Or, adding a second target track point to the second behavior track.
In one embodiment, as shown in FIG. 12, the build module 10 includes:
and the second generation submodule 11 is configured to generate an initial coordinate point based on a longitude coordinate axis and a latitude coordinate axis of the space-time coordinate system according to each piece of location information.
And the forming submodule 12 is used for arranging the initial coordinate points in time sequence based on the time coordinate axis of the space-time coordinate system according to the time information corresponding to the position information to form a plurality of track points.
And the constructing submodule 13 is configured to construct the first behavior trace and the second behavior trace based on the plurality of track points.
In one embodiment, the preset edit distance algorithm for changing one track point on the second behavior track into the second target track point in the generating unit 2021 is as follows:
wherein, L (P)1，P2) Preset edit distance, P, representing points of change trajectory1Representing a point of the second line, P2Representing a second target track point, x1Is P1Coordinate in the X axis, y1Is P1Coordinate in the Y axis, x2Is P2Coordinate in the X axis, y2Is P2Coordinates on the Y-axis.
In one embodiment, the preset edit distance algorithm for adding a second target track point to the second behavior track in the generating unit 2021 is as follows:
wherein, AL (P)k) Preset edit distance, P, representing incremental track pointskIndicating an increased second target track point, PiRepresenting a track point, P, on the second behavior track that precedes the second target track pointjOne trace point, L (P), on the second behavior trace after the second target trace point is representedi，Pk) Representing points of track PiAnd the track point PkEdit distance between, L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
In one embodiment, the preset edit distance algorithm for removing the redundant track point on the second behavior track in the fourth computation submodule 208 is:
wherein DL (P)k) Indicating a preset edit distance, P, for removing redundant trace pointskRepresenting redundant points of track, PiRepresenting a trace point, P, preceding the redundant trace point on the second behavior tracejRepresenting a trace point, L (P), on the second behavior trace after the redundant trace pointi，Pk) Representing points of track PiAnd the track point PkEdit distance between, L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
In one example, the calculation module 20 is configured to calculate the minimum edit distance for the second behavior trace to be converted into the first behavior trace, and may use the following formula:
wherein, E (P)a，Qb) Indicating cut-off to trace point PaFirst action track and cut-off to track point QbThe edit distance between the second behavior trace. AL (P)a) Indicating increasing of the trace point Pa。AL(Qb) Indicating increasing of trace point Qb。E(Pa-1，Qb-1) Indicating cut-off to trace point Pa-1First action track and cut-off to track point Qb-1The edit distance between the second behavior trace. E (P)a-1，Qb) Indicating cut-off to trace point Pa-1First action track and cut-off to track point QbThe edit distance between the second behavior trace. E (P)a，Qb-1) Indicating cut-off to trace point PaFirst action track and cut-off to track point Qb-1The edit distance between the second behavior trace. L (P)a，Qb) Representing points of track PaTo the track point QbThe minimum edit distance. a represents the a track point of the first behavior track, b represents the b track point of the second behavior track, m represents the last track point of the first behavior track, and n represents the last track point of the second behavior track.
E(Pa，Qb)＝E(Pa-1，Qb-1) The meaning of (A) is: point of track PaAnd QbAnd (4) overlapping, wherein the increment of the two action tracks is 0 at the moment, so that only the cutoff track point P needs to be calculateda-1First action track and cut-off to track point Qb-1The edit distance between the second behavior trace.
E(Pa，Qb)＝E(Pa-1，Qb-1)+L(Pa，Qb) The meaning of (A) is: calculating the tracing point PaTo the track point QbMinimum edit distance of, and cut-off to, the track point Pa-1First action track and cut-off to track point Qb-1The minimum edit distance between the second behavior trace.
E(Pa，Qb)＝E(Pa-1，Qb)+AL(Pa) The meaning of (A) is: calculating and adding track points P on the second behavior trackaEdit distance of, and cut to, track point Pa-1First action track and cut-off to track point QbThe minimum edit distance between the second behavior trace.
E(Pa，Qb)＝E(Pa，Qb-1)+AL(Qb) The meaning of (A) is: calculating and adding track points Q on the first behavior trackbEdit distance of, and cut to, track point PaFirst action track and cut-off to track point Qb-1The edit distance between the second behavior trace.
It should be noted that the trajectory similarity determining apparatus 100 provided by the present application may implement any of the above embodiments of the trajectory similarity determining method.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
Fig. 13 is a block diagram of an electronic device according to the method for determining track similarity according to the embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 13, the electronic apparatus includes: one or more processors 901, memory 902, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display Graphical information for a Graphical User Interface (GUI) on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 13 illustrates an example of a processor 901.
The memory 902, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the method for determining trajectory similarity in the embodiments of the present application (for example, the building module 10, the calculating module 20, and the determining module 30 shown in fig. 8). The processor 901 executes various functional applications of the server and data processing, i.e. a method for determining the trajectory similarity in the above method embodiments, by running non-transitory software programs, instructions and modules stored in the memory 902.
The memory 902 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the electronic device determined according to the track similarity, and the like. Additionally, the memory Y02 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 902 may optionally include memory remotely located from the processor 901, which may be connected to the trajectory similarity determination electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the method for determining track similarity may further include: an input device 903 and an output device 904. The processor 901, the memory 902, the input device 903, and the output device 904 may be connected by a bus or other means, and fig. 13 illustrates examples of connection by a bus.
The input device 903 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device determined by the similarity of the trajectory, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointer, one or more mouse buttons, a track ball, a joystick, or other input device. The output devices 904 may include a display device, auxiliary lighting devices (e.g., LEDs), tactile feedback devices (e.g., vibrating motors), and the like. The Display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) Display, and a plasma Display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, Application Specific Integrated Circuits (ASICs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (Cathode Ray Tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
According to the technical scheme of the embodiment of the application, the technical means that the behavior tracks are constructed in the space-time coordinate system by utilizing the position information and the time information and the similarity of the two behavior tracks is calculated based on the minimum editing distance are adopted, so that the technical problem that the time factor is ignored when the behavior tracks are constructed and analyzed in the two-dimensional plane coordinate system is solved, and the technical effect of more accurately obtaining the behavior track similarity of the target object is achieved.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (16)
1. A track similarity determination method is characterized by comprising the following steps:
constructing a first behavior track and a second behavior track in a space-time coordinate system according to position information and time information in the target object behavior data;
for any first track point on the first behavior track and any second track point on the second behavior track, determining an editing distance between the first track point and the second track point under the condition that the time distance between the first track point and the second track point is less than or equal to a time threshold;
calculating a minimum editing distance for converting the second behavior track into the first behavior track based on each editing distance;
and determining the similarity between the first behavior track and the second behavior track according to the minimum editing distance.
2. The method of claim 1, wherein calculating the minimum edit distance for the second behavior trace to transition to the first behavior trace based on the trace points of the first behavior trace comprises:
determining a first target track point on the first behavior track;
generating a second target track point on the second behavior track, wherein the second target track point has the same coordinate as the first target track point;
calculating and generating a first editing distance of the second target track point according to a preset editing distance algorithm;
calculating a second editing distance of a second behavior track before the second target track point converted into a first behavior track before the first target track point by using a recursive solving algorithm;
and calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the first editing distance and the second editing distance.
3. The method of claim 1, wherein calculating the minimum edit distance for the second behavior trace to transition to the first behavior trace based on the trace points of the first behavior trace comprises:
determining a third target track point and a fourth target track point on the first behavior track;
removing redundant track points on the second behavior track, wherein the redundant track points are track points with time coordinates between time coordinates of the third target track point and the fourth target track point;
calculating a third editing distance for removing the redundant track points according to a preset editing distance algorithm;
calculating a fourth editing distance of the first behavior track before the second behavior track before the redundant track point is converted into the third target track point by using a recursive solving algorithm;
and calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the third editing distance and the fourth editing distance.
4. The method of claim 2, wherein generating a second target trajectory point on the second behavior trace comprises:
changing one track point on the second behavior track into the second target track point; or the like, or, alternatively,
and adding one second target track point on the second behavior track.
5. The method according to claim 4, wherein the preset edit distance algorithm for changing one track point on the second behavior track to the second target track point is:
wherein, L (P)1，P2) Preset edit distance, P, representing points of change trajectory1Representing a trace point, P, on said second behavior trace2Representing said second target track point, x1Is P1Coordinate in the X axis, y1Is P1Coordinate in the Y axis, x2Is P2Coordinate in the X axis, y2Is P2Coordinates on the Y-axis.
6. The method according to claim 4, wherein the preset edit distance algorithm for adding one second target track point to the second behavior track is as follows:
wherein, AL (P)k) Preset edit distance, P, representing incremental track pointskRepresenting increased second target track point, PiRepresenting a track point, P, on said second behavior track that precedes said second target track pointjRepresents a track point, L (P), on the second behavior track that is located after the second target track pointi，Pk) Representing points of track PiAnd the track point PkEdit distance between, L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
7. The method according to claim 3, wherein the preset edit distance algorithm for removing the redundant track points on the second behavior track is:
wherein DL (P)k) Indicating a preset edit distance, P, for removing redundant trace pointskRepresenting said redundant trace points, PiRepresenting a trace point, P, on said second behavior trace preceding said redundant trace pointjRepresents a trace point, L (P), on the second behavior trace that follows the redundant trace pointi，Pk) Representing points of track PiAnd the track point PkEdit distance between, L (P)k，Pj) Representing points of track PkAnd the track point PjThe edit distance between.
8. The method of claim 1, wherein constructing the first behavior trace and the second behavior trace in a spatio-temporal coordinate system according to the position information and the time information in the target object behavior data comprises:
generating an initial coordinate point based on a longitude coordinate axis and a latitude coordinate axis of the space-time coordinate system according to the position information;
arranging the initial coordinate points according to time sequence based on the time coordinate axis of the space-time coordinate system according to the time information corresponding to the position information to form a plurality of track points;
and constructing the first behavior track and the second behavior track based on the plurality of track points.
9. The method of claim 8, wherein before generating the initial coordinate point based on a longitude coordinate axis and a latitude coordinate axis of the spatio-temporal coordinate system according to each of the location information, further comprising:
unifying the measurement units of the position information into longitude and latitude units;
and unifying the measurement units of the time information.
10. An apparatus for trajectory similarity determination, comprising:
the building module is used for building a first behavior track and a second behavior track in a space-time coordinate system according to the position information and the time information in the target object behavior data;
the distance determining module is used for determining the editing distance between a first track point and a second track point under the condition that the time distance between the first track point and the second track point is smaller than or equal to a time threshold value for any first track point on the first action track and any second track point on the second action track;
the calculation module is used for calculating the minimum editing distance for converting the second behavior track into the first behavior track based on each editing distance;
and the determining module is used for determining the similarity between the first behavior track and the second behavior track according to the minimum editing distance.
11. The apparatus of claim 10, wherein the computing module comprises:
the first determining submodule is used for determining a first target track point on the first behavior track;
the first generation submodule is used for generating a second target track point on the second behavior track, and the coordinates of the second target track point are the same as those of the first target track point;
the first calculation submodule is used for calculating and generating a first editing distance of the second target track point according to a preset editing distance algorithm;
the second calculation submodule is used for calculating a second editing distance of a second behavior track before the second target track point converted into a first behavior track before the first target track point by using a recursive solving algorithm;
and the third calculation submodule is used for calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the first editing distance and the second editing distance.
12. The apparatus of claim 10, wherein the computing module comprises:
the second determining submodule is used for determining a third target track point and a fourth target track point on the first behavior track;
the removing submodule is used for removing redundant track points on the second behavior track, wherein the redundant track points are track points of which the time coordinates are between the time coordinates of the third target track point and the fourth target track point;
the fourth calculation submodule is used for calculating a third editing distance for removing the redundant track points according to a preset editing distance algorithm;
the fifth calculation submodule is used for calculating a fourth editing distance of the second behavior track before the redundant track point is converted into the first behavior track before the third target track point by using a recursive solving algorithm;
and the sixth calculating sub-module is used for calculating the minimum editing distance for converting the second behavior track into the first behavior track according to the third editing distance and the fourth editing distance.
13. The apparatus of claim 11, wherein the first generation submodule comprises:
a generating unit, configured to change one track point on the second behavior track into the second target track point; or, adding one second target track point to the second behavior track.
14. The apparatus of claim 10, wherein the building module comprises:
the second generation submodule is used for generating an initial coordinate point based on a longitude coordinate axis and a latitude coordinate axis of the space-time coordinate system according to the position information;
the forming submodule is used for arranging the initial coordinate points according to time sequence on the basis of the time coordinate axis of the space-time coordinate system according to the time information corresponding to the position information to form a plurality of track points;
and the constructing submodule is used for constructing the first behavior track and the second behavior track based on the plurality of track points.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.
16. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-9.
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| CN111414444A (en) * | 2020-03-02 | 2020-07-14 | 北京明略软件系统有限公司 | Method and device for processing space-time trajectory information |
| CN111930791B (en) * | 2020-05-28 | 2022-07-15 | 中南大学 | Similarity calculation method and system for vehicle track and storage medium |
| CN111797295B (en) * | 2020-06-19 | 2021-04-02 | 云从科技集团股份有限公司 | Multi-dimensional space-time trajectory fusion method and device, machine readable medium and equipment |
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| CN112037245B (en) * | 2020-07-22 | 2023-09-01 | 杭州海康威视数字技术股份有限公司 | Method and system for determining similarity of tracked targets |
| CN112561948B (en) * | 2020-12-22 | 2023-11-21 | 中国联合网络通信集团有限公司 | Space-time trajectory-based accompanying trajectory recognition method, device and storage medium |
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