efficiently retrieving longest common route patterns of moving objects by summarizing turning regions

	efficiently retrieving longest common route patterns of moving objects by summarizing turning regions
	Huang Guangyan; Zhang Yanchun; He Jing; Ding Zhiming
	2011
会议名称	15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011
会议录名称	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
页码	375-386
会议日期	24-May-20
会议地点	Shenzhen, China
收录类别	EI
出版地	Germany
ISSN	3029743
ISBN	9783642208409
部门归属	(1) Centre for Applied Informatics, School of Engineering and Science, Victoria University, Australia; (2) Institute of Software, Chinese Academy of Sciences, China
摘要	The popularity of online location services provides opportunities to discover useful knowledge from trajectories of moving objects. This paper addresses the problem of mining longest common route (LCR) patterns. As a trajectory of a moving object is generally represented by a sequence of discrete locations sampled with an interval, the different trajectory instances along the same route may be denoted by different sequences of points (location, timestamp). Thus, the most challenging task in the mining process is to abstract trajectories by the right points. We propose a novel mining algorithm for LCR patterns based on turning regions (LCRTurning), which discovers a sequence of turning regions to abstract a trajectory and then maps the problem into the traditional problem of mining longest common subsequences (LCS). Effectiveness of LCRTurning algorithm is validated by an experimental study based on various sizes of simulated moving objects datasets. © 2011 Springer-Verlag.
关键词	Abstracting Algorithms Fading (Radio) Mining Trajectories
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/14313
专题	基础软件国家工程研究中心
推荐引用方式 GB/T 7714	Huang Guangyan,Zhang Yanchun,He Jing,et al. efficiently retrieving longest common route patterns of moving objects by summarizing turning regions[C]. Germany,2011:375-386.

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
efficiently retrievi（293KB）			开放获取	--	请求全文