Paper Info
Title
STMPE: an efficient movement pattern extraction algorithm for spatio-temporal data mining
Abstract
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.
Year
DOI
Venue
2006
10.1007/11751588_28
ICCSA
Keywords
Field
DocType
existing movement pattern extraction,spatio-temporal data,movement pattern,efficient movement pattern extraction,spatio-temporal movement pattern extraction,large capacity,stmpe algorithm,short-term movement pattern,performance evaluation,spatio-temporal data mining,candidate movement pattern,location based service
Mobile computing,Data mining,Computer science,Extraction algorithm,Location-based service,Temporal database,Artificial intelligence,Temporal data mining,Mathematical optimization,Regular expression,Pattern recognition,Information extraction,Telematics
Conference
Volume
ISSN
ISBN
3981
0302-9743
3-540-34072-6
Citations 
PageRank 
References 
2
0.39
8
Authors
5
Name
Order
Citations
PageRank
Dong-Oh Kim1156.72
Hong-Koo Kang283.91
Dong-Suk Hong3103.67
Jae-Kwan Yun4164.32
Ki-Joon Han5266.76