Dwell-time-based moving object semantic behavior pattern mining method

A technology of moving objects and dwell time, which is applied in structured data retrieval, instrumentation, electronic digital data processing, etc., can solve the problem of not considering the dwell time of moving objects, being unable to accurately distinguish the semantic behavior patterns of moving objects, and failing to obtain effective research and problem solving

Active Publication Date: 2015-12-02
INST OF SOFTWARE - CHINESE ACAD OF SCI
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Problems solved by technology

[0004] However, the above studies did not consider the dwell time of moving objects at each stop point, and cannot accurately distinguish the different semantic behavior patterns among moving objects.
The definition and description of the semantic behavior pattern of movi

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  • Dwell-time-based moving object semantic behavior pattern mining method
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  • Dwell-time-based moving object semantic behavior pattern mining method

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[0059] In the following, with reference to the accompanying drawings, the present invention is further illustrated by examples, but the scope of the present invention is not limited in any way.

[0060] The overall structure of the present invention is as figure 1 As shown, the principle is:

[0061] Firstly, in a series of semantic trajectory collections of moving objects, the frequent semantic behavior patterns based on residence time of each moving object are excavated. In the present invention, the semantic trajectory of a moving object is an ordered sequence S composed of a set of semantic points, where the semantic point point=(A, t), A represents the stay point of the moving object, and t represents the stay time of the moving object in A. Table 1 shows a semantic trajectory set D, including four semantic trajectories. The semantic behavior pattern is an ordered sequence P composed of a set of semantic points, and P satisfies: the number of semantic trajectories matching ...

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Abstract

The invention relates to a dwell-time-based moving object semantic behavior pattern mining method, which comprises the following steps of: (1) collecting semantic track data of moving objects, and storing semantic information of the moving objects; (2) for each moving object, mining all frequent semantic behavior patterns of each moving object; (3) designing a time-weight-based semantic behavior pattern similarity degree measurement method, and calculating the similarity degree between the frequent semantic behavior patterns; and (4) according to the similarity degree between the frequent semantic behavior patterns, using a pruning strategy for hierarchical clustering, and mining all moving object clustering with the similar semantic behavior patterns. The method has the advantage that high accuracy and high efficiency of the moving object semantic behavior pattern mining can be ensured. The final result can be provided for a user in relevant fields to be used, such as a friend recommending system, the track case cracking field and the individualized service field; the accurate finding on the similar semantic behavior patterns of mobile object groups can be supported; and the error rate is reduced.

Description

technical field [0001] The invention relates to the field of research and application of mobile object data mining, in particular to a method for mining semantic behavior patterns of mobile objects based on dwell time. Background technique [0002] In recent years, the trajectory pattern mining technology of moving objects has attracted much attention. The trajectory of moving objects records people's activities in the real world, and these activities reflect people's lifestyles and behavior habits to a certain extent. Therefore, by analyzing the trajectory data Analyzing, digging out the behavior patterns of moving objects, and discovering the correlation between moving objects has important research value and wide application fields. [0003] The current trajectory pattern mining methods of moving objects are mainly divided into two categories: trajectory pattern mining based on geographic information and trajectory pattern mining based on semantic information. Among them...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/29G06F16/35
Inventor 郭黎敏郭皓明徐怀野
Owner INST OF SOFTWARE - CHINESE ACAD OF SCI
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