文章基本信息

标题：On Mining Movement Pattern from Mobile Users
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作者：David Taniar ; John Goh
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2007
卷号：3
DOI：10.1080/15501320601069499
出版社：Hindawi Publishing Corporation
摘要：In the era in which activities performed by mobile users are tracked through various sensing mechanisms, the movement data collected through these sensors is submitted into a data mining algorithm in order to determine the movement pattern. The movement pattern refers to the pattern that mobile users generally take to move from one base location to another base location through multiple intermediate locations. This paper provides a proposal and case study on how the movement pattern can be extracted from mobile users through transforming the user movement database to the location movement database and subsequently transferred to an algorithm Apriori-like movement pattern (AMP) and movement tree (M-tree). The result is a list of sequences in which mobile users frequently go through that which satisfies min-support and min-confidence. The result of this movement pattern mining exercise opens up a new future for the prediction of the movement for the individual mobile user.