2005 공간정보시스템학회 추계학술대회
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| 한글제목(Korean Title) |
An Efficient Algorithm for Mining Frequent Sequences In Spatiotemporal Data |
| 영문제목(English Title) |
An Efficient Algorithm for Mining Frequent Sequences In Spatiotemporal Data |
| 저자(Author) |
Vu Thi Hong Nhan
Cheong Hee Chi
Keun Ho Ryu
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| 원문수록처(Citation) |
VOL 00 NO. 00 PP. 0061 ~ 0066 (2005. 00) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine learning, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more computationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service
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