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

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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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 moving objects based on the residence time, the extraction and mining of the semantic behavior pattern, the realization and performance analysis of the prototype system, etc. have not been effectively researched and solved, and these key technical issues need further research

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