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Erschienen in:
2006 | OriginalPaper | Buchkapitel
STMPE: An Efficient Movement Pattern Extraction Algorithm for Spatio-temporal Data Mining
verfasst von : Dong-Oh Kim, Hong-Koo Kang, Dong-Suk Hong, Jae-Kwan Yun, Ki-Joon Han
Erschienen in: Computational Science and Its Applications - ICCSA 2006
Verlag: Springer Berlin Heidelberg
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With the recent development of LBS(Location Based Service) and Telematics, the use of spatio-temporal data mining which extracts useful knowledge such as movement patterns of moving objects gets increasing. However, the existing movement pattern extraction methods including STPMine1 and STPMine2 create lots of candidate movement patterns when the minimum support is low. As a result of that, the performance of time and space is sharply increased as a weak point. Therefore, in this paper, we suggest the STMPE (Spatio-Temporal Movement Pattern Extraction) algorithm in order to efficiently extract movement patterns of moving objects from the large capacity of spatio-temporal data. The STMPE algorithm generalizes spatio-temporal data and minimizes the use of memory. Because it produces and maintains short-term movement patterns, the frequency of database scan can be minimized. Actually, the STMPE algorithm was improved twice to 10 times better than STPMine1 and STPMine2 from the result of performance evaluation.