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http://dx.doi.org/10.3745/KIPSTD.2008.15-D.2.179

Discovery of Frequent Sequence Pattern in Moving Object Databases  

Vu, Thi Hong Nhan (한국전자통신연구원, RFID/USN 미들웨어 연구팀)
Lee, Bum-Ju (충북대학교 전기전자컴퓨터공학부 전자계산학과)
Ryu, Keun-Ho (충북대학교 전기전자 및 컴퓨터공학부)
Publication Information
The KIPS Transactions:PartD / v.15D, no.2, 2008 , pp. 179-186 More about this Journal
Abstract
The converge of location-aware devices, GIS functionalities and the increasing accuracy and availability of positioning technologies pave the way to a range of new types of location-based services. The field of spatiotemporal data mining where relationships are defined by spatial and temporal aspect of data is encountering big challenges since the increased search space of knowledge. Therefore, we aim to propose algorithms for mining spatiotemporal patterns in mobile environment in this paper. Moving patterns are generated utilizing two algorithms called All_MOP and Max_MOP. The first one mines all frequent patterns and the other discovers only maximal frequent patterns. Our proposed approach is able to reduce consuming time through comparison with DFS_MINE algorithm. In addition, our approach is applicable to location-based services such as tourist service, traffic service, and so on.
Keywords
Spatiotemporal Data Mining; Moving Object; Frequent Patterns;
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Times Cited By KSCI : 1  (Citation Analysis)
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