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http://dx.doi.org/10.5762/KAIS.2011.12.1.451

Location Generalization of Moving Objects for the Extraction of Significant Patterns  

Lee, Yon-Sik (Dept. of Computer Information Engineering, Kunsan National University)
Ko, Hyun (Korea Aerospace Research Institute)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.12, no.1, 2011 , pp. 451-458 More about this Journal
Abstract
In order to provide the optimal location based services such as the optimal moving path search or the scheduling pattern prediction, the extraction of significant moving pattern which is considered the temporal and spatial properties of the location-based historical data of the moving objects is essential. In this paper, for the extraction of significant moving pattern we propose the location generalization method which translates the location attributes of moving object into the spatial scope information based on $R^*$-tree for more efficient patterning the continuous changes of the location of moving objects and for indexing to the 2-dimensional spatial scope. The proposed method generates the moving sequences which is satisfied the constraints of the time interval between the spatial scopes using the generalized spatial data, and extracts the significant moving patterns using them. And it can be an efficient method for the temporal pattern mining or the analysis of moving transition of the moving objects to provide the optimal location based services.
Keywords
Moving Object; Moving Pattern; Location Generalization; Extraction of Significant Moving Pattern;
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Times Cited By KSCI : 6  (Citation Analysis)
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1 H. Cao, N. Mamoulis and D. W. Cheung, "Mining Frequent Spatio-Temporal Sequential Patterns", in proc. on the 5th IEEE International Conference on Data Mining(ICDM), pp. 82-89, 2005.   DOI
2 D. O. Kim, H. K. Kang, D. S. Hong, J. K. Yun and K. J. Han, "STMPE : An Efficient Movement Pattern Extraction Algorithm for Spatio-temporal Data Mining", in proc. on International Conference on Computational Science and Its Applications(ICCSA), pp. 259-269, 2006.
3 이준욱, "위치 기반 서비스를 위한 이동 객체의 시간 패턴 탐사", 한국정보과학회논문지, 제29권, 제5 호, 2002.   과학기술학회마을
4 한선영, "시공간 이동 시퀀스 패턴 마이닝 기법", 이화여자대학교 대학원, 석사학위논문, 2006.
5 고현, 김광종, 이연식, "R* Tree와 Grid를 이용한이동 객체의 위치 일반화 기법", 한국컴퓨터정보학회논문지, 제12권 2호, pp. 231-242, 2007. 5   과학기술학회마을
6 고 현, 이연식, "이동 시퀀스의 빈발도를 이용한 최적 이동 패턴 탐사 기법", 한국정보처리학회 논문지, 제16-D권, 제1호, 2009.   과학기술학회마을   DOI
7 이연식, 박성숙, "시퀀스 빈발도와 가중치를 이용한 최적 이동 패턴 탐사" 한국인터넷정보학회논문지, 제10권 제5호, pp. 79-93, 2009. 10   과학기술학회마을
8 안윤애, 김동호, 류근호, "차량위치 추적을 위한 이동 객체 관리 시스템의 설계", 정보처리학회논문지D, 제9-D권 제5호, 2002.
9 N. Mamoulis, H. Cao, G. Kollios, M. Hadjieleftheriou, Y. Tao and D. W. Cheung, "Mining, Indexing and Querying Historical Spatio-Temporal Data", in proc. on the International Conference on Knowledge Discovery and Data Mining, 2004.
10 D. Pfoser, C. S. Jensen, and Y. Theodoridis, "Novel Approaches in Query Processing for Moving Objects", Proc. of the Int'1 Conf. on VLDB, 2000.
11 J. Gudmundsson, M. V. Kreveld and B. Speckmann, "Efficient Detection of Motion Patterns in Spatio-Temporal Data Sets", in proc. on the 12th annual ACM international workshop on Geographic Information Systems(GIS), pp. 250-257, 2004.
12 Y. Huang, L. Zhang and P. Zhang, "Finding Sequential Patterns from a Massive Number of Spatio-Temporal Events", SDM, SIAM, 2006.
13 J. D. Chung, O. H. Paek, J. W. Lee, K. H. Ryu, "Temporal Pattern Mining of Moving Objects for Location-Based Service", Proc. of the 13th International Conference on Database and Expert Systems Applications, p. 331-340, September 02-06, 2002.
14 J. W. Lee, O. H. Paek, K. H. Ryu, "Temporal Moving Pattern Mining for Location-based Service", The Journal of Systems and Software, Vol. 73. 2004.