Flexible Similarity Search for Enriched Trajectories

Hideaki Ohashi, Toshiyuki Shimizu, Masatoshi Yoshikawa

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

In this study, we focus on a method of searching for similar trajectories. In most previous works on searching for similar trajectories, only raw trajectory data have been used. However, to obtain deeper insights, additional time-dependent trajectory features should be utilized depending on the search intent. For instance, to identify soccer players who have similar dribbling patterns, such additional features include the correlations between players' speeds and directions. In addition, when finding similar combination plays, the additional features include the team players' movements. In this paper, we develop a framework to flexibly search for similar trajectories associated with time-dependent features, called enriched trajectories. In this framework, weights, which represent the relative importance of each feature, can be flexibly input. Moreover, to facilitate fast searching, we propose a lower bounding measure of the DTW distance between enriched trajectories. We evaluate the effectiveness of the lower bounding measure using soccer data and synthetic data. Our experimental results suggest that the proposed lower bounding measure is superior to the existing measure and works very well.

本文言語英語
ホスト出版物のタイトルProceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
編集者Carlotta Domeniconi, Francesco Gullo, Francesco Bonchi, Francesco Bonchi, Josep Domingo-Ferrer, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Zhi-Hua Zhou, Xindong Wu
出版社IEEE Computer Society
ページ1139-1144
ページ数6
ISBN(電子版)9781509054725
DOI
出版ステータス出版済み - 7 2 2016
外部発表はい
イベント16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 - Barcelona, スペイン
継続期間: 12 12 201612 15 2016

出版物シリーズ

名前IEEE International Conference on Data Mining Workshops, ICDMW
0
ISSN(印刷版)2375-9232
ISSN(電子版)2375-9259

会議

会議16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
国/地域スペイン
CityBarcelona
Period12/12/1612/15/16

All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンスの応用
  • ソフトウェア

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