Mining Spatial-Temporal Semantic Trajectory Patterns from Raw Trajectories

Chien Cheng Chen, Chia Hsiang Kuo, Wen-Chih Peng

研究成果: Conference contribution同行評審

10 引文 斯高帕斯(Scopus)

摘要

With the development of GPS and the popularity of smart phones and wearable devices, users can easily log their daily trajectories. Prior works have elaborated on mining trajectory patterns from raw trajectories. However, trajectory patterns do not have explicit time information or semantic information. To enrich trajectory patterns, we propose STS-TPs (standing for Spatial-Temporal Semantic Trajectory Patterns) which refer to the moving patterns with spatial, temporal, and semantic attributes. Given a set of user trajectories, we aim at mining STS-TPs. Explicitly, we extract the three attributes from raw trajectories, and convert these trajectories into semantic trajectory sequences. Given a set of such semantic trajectory sequences, STS-TPs could be viewed as sequential patterns with multiple attributes. To fully explore the efficiency of PrefixSpan on sequential pattern mining, we propose a PrefixSpan-based algorithm (abbreviated as PS) to discover STS-TPs. Note that the input for PrefixSpan is a set of sequences consisting of items. However, each item of semantic trajectory sequences contains three attributes, and we need to further transform these sequences into symbolized sequences before using PrefixSpan. Therefore, we propose two algorithms of Sequence Symbolization (SS) and Advanced Sequence Symbolization (ASS) to achieve this purpose. In light of STS-TPs, we further propose query tasks to predict users' behaviors. To evaluate our proposed algorithms, we conducted experiments on the real datasets of Google Location History, and the experimental results show the effectiveness and efficiency of our proposed algorithms.

原文English
主出版物標題Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
編輯Xindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1019-1024
頁數6
ISBN(電子)9781467384926
DOIs
出版狀態Published - 29 1月 2016
事件15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States
持續時間: 14 11月 201517 11月 2015

出版系列

名字Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Conference

Conference15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
國家/地區United States
城市Atlantic City
期間14/11/1517/11/15

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