Moving Sequential Pattern Mining Based on Spatial Constraints in Mobile Environment

摘要：

Moving sequential pattern mining is important in the trajectory analysis of moving objects and mobility prediction in mobile environment. The traditional sequential pattern mining method-PrefixSpan, is not applicable to the spatial constrained applications and it will produce a large number of duplicated projected databases in mining data sets. In order to overcome these drawbacks, a new algorithm is proposed, named Sequential Mining of Moving Patterns Based on Spatial Constraints in Mobile Environment (named SMPM). This algorithm has a property of spatial constraints, records the first position of the suffix in the sequence, and can avoid mining the same projected database and avoid physical projection according to the suffixs position and spatial constraints.

关键词： data mining moving sequential pattern suffix prosition spatial constraint

作者: Yong-Gui Zou Hong Yu

作者单位: Sino-Korea Chongqing GIS Research Center,College of Computer Science and Technology,Chongqing University of Posts and Telecommunications Chongqing, 400065, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 103-107

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）