文章基本信息

标题：Self Organizing Map based Clustering Approach for Trajectory Data
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作者：Sanjiv Kumar Shukla ; Sourabh Rungta ; Lokesh Kumar Sharma 等
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2012
卷号：3
期号：3-1
页码：311-316 Issue 2012 .ISSN 2231
出版社：Seventh Sense Research Group
摘要：Clustering algorithm for the moving or trajectory data provides new and helpful information. It has wide application on various location aware services. In this study the Self Organizing Map is used to form the cluster on trajectory data. The selforganizing map (SOM) is an important tool in exploratory phase of data mining. It projects input space on prototypes of a lowdimensional regular grid that can be effectively utilized to visualize and explore properties of the data. When the number of SOM units is large, to facilitate quantitative analysis of the map and the data, similar units need to be grouped, i.e., clustered.
关键词：Trajectory Data; Self-Organizing Map; Clustering