ISCAS OpenIR
user oriented trajectory similarity search
Wang Haibo; Liu Kuien
2012
Conference NameInternational Workshop on Urban Computing, UrbComp 2012 - Held in Conjunctionwith KDD 2012
SourceProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages103-110
Conference DateAugust 12, 2012 - August 12, 2012
Conference PlaceBeijing, China
Indexed TypeEI
ISBN9781450315425
Department(1) School of Information Technology and Electrical Engineering University of Queensland Australia; (2) Institute of Software Chinese Academy of Sciences China
English AbstractTrajectory 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.; 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.
KeywordData Mining
SponsorshipACM Spec. Interest Group Knowl. Discov. Data (SIGKDD); ACM Special Interest Group on Management of Data (SIGMOD)
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15791
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Wang Haibo,Liu Kuien. user oriented trajectory similarity search[C],2012:103-110.
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