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Title:
user oriented trajectory similarity search
Author: Wang Haibo ; Liu Kuien
Source: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Conference Name: International Workshop on Urban Computing, UrbComp 2012 - Held in Conjunctionwith KDD 2012
Conference Date: August 12, 2012 - August 12, 2012
Issued Date: 2012
Conference Place: Beijing, China
Keyword: Data mining
Indexed Type: EI
ISBN: 9781450315425
Department: (1) School of Information Technology and Electrical Engineering University of Queensland Australia; (2) Institute of Software Chinese Academy of Sciences China
Sponsorship: ACM Spec. Interest Group Knowl. Discov. Data (SIGKDD); ACM Special Interest Group on Management of Data (SIGMOD)
Abstract: Trajectory similarity search studies the problem of finding a trajectory from the database such the found trajectory most similar to the query trajectory. Past research mainly focused on two aspects: shape similarity search and semantic similarity search, leaving personalized similarity search untouched. In this paper, we propose a new query which takes user's preference into consideration to provide personalized searching. We define a new data model for this query and identify the efficiency issue as the key challenge: given a user specified trajectory, how to efficiently retrieve the most similar trajectory from the database. By taking advantage of the spatial localities, we develop a two-phase algorithm to tame this challenge. Two optimized strategies are also developed to speed up the query process. Both the theoretical analysis and the experiments demonstrate the high efficiency of the proposed method. © 2012 ACM.
English Abstract: Trajectory similarity search studies the problem of finding a trajectory from the database such the found trajectory most similar to the query trajectory. Past research mainly focused on two aspects: shape similarity search and semantic similarity search, leaving personalized similarity search untouched. In this paper, we propose a new query which takes user's preference into consideration to provide personalized searching. We define a new data model for this query and identify the efficiency issue as the key challenge: given a user specified trajectory, how to efficiently retrieve the most similar trajectory from the database. By taking advantage of the spatial localities, we develop a two-phase algorithm to tame this challenge. Two optimized strategies are also developed to speed up the query process. Both the theoretical analysis and the experiments demonstrate the high efficiency of the proposed method. © 2012 ACM.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15791
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Wang Haibo,Liu Kuien. user oriented trajectory similarity search[C]. 见:International Workshop on Urban Computing, UrbComp 2012 - Held in Conjunctionwith KDD 2012. Beijing, China. August 12, 2012 - August 12, 2012.
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