Clustering and Aggregating Clues of Trajectories for Trajectory Pattern Mining

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 期刊論文 > Item 987654321/106210

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题名:	Clustering and Aggregating Clues of Trajectories for Trajectory Pattern Mining
作者:	Hung, Chih-Chieh;Peng, Wen-Chih;Lee, Wang-Chien
关键词:	Trajectory pattern mining;Trajectory similarity;Trajectory clustering
日期:	2015-04-01
上传时间:	2016-04-22 13:41:56 (UTC+8)
出版者:	A C M Special Interest Group
摘要:	In this paper, we propose a new trajectory pattern mining framework, namely Clustering and Aggregating Clues of Trajectories (CACT), for discovering trajectory routes that represent the frequent movement behaviors of a user. In addition to spatial and temporal biases, we observe that trajectories contain silent durations, i.e., the time durations when no data points are available to describe the movements of users, which bring many challenging issues to trajectory pattern mining. We claim that a movement behavior would leave some clues in its various sampled/observed trajectories. These clues may be extracted from spatially and temporally co-located data points from the observed trajectories. Based on this observation, we propose clue-aware trajectory similarity to measure the clues between two trajectories. Accordingly, we further propose the clue-aware trajectory clustering algorithm to cluster similar trajectories into groups to capture the movement behaviors of the user. Finally, we devise the clue-aware trajectory aggregation algorithm to aggregate trajectories in the same group to derive the corresponding trajectory pattern and route. We validate our ideas and evaluate the proposed CACT framework by experiments using both synthetic and real datasets. The experimental results show that CACT is more effective in discovering trajectory patterns than the state-of-the-art techniques for mining trajectory patterns.
關聯:	VLDB JOURNAL 24(2), pp.162-192
显示于类别:	[資訊工程學系暨研究所] 期刊論文

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