user oriented trajectory similarity search
文献类型：会议论文
| 作者 | Wang Haibo ; Liu Kuien |
| 出版日期 | 2012 |
| 会议名称 | International Workshop on Urban Computing, UrbComp 2012 - Held in Conjunctionwith KDD 2012 |
| 会议日期 | August 12, 2012 - August 12, 2012 |
| 会议地点 | Beijing, China |
| 关键词 | Data mining |
| 页码 | 103-110 |
| 中文摘要 | 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. |
| 英文摘要 | 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. |
| 收录类别 | EI |
| 会议主办者 | ACM Spec. Interest Group Knowl. Discov. Data (SIGKDD); ACM Special Interest Group on Management of Data (SIGMOD) |
| 会议录 | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
 |
| 语种 | 英语 |
| ISBN号 | 9781450315425 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15791]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | 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. |
入库方式： OAI收割
来源：软件研究所
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