Browse > Article
http://dx.doi.org/10.3745/KIPSTD.2009.16-D.1.113

A Method for Optimal Moving Pattern Mining using Frequency of Moving Sequence  

Lee, Yon-Sik (군산대학교 컴퓨터정보공학과)
Ko, Hyun (한국항공우주연구원 프로젝트연구원)
Publication Information
The KIPS Transactions:PartD / v.16D, no.1, 2009 , pp. 113-122 More about this Journal
Abstract
Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.
Keywords
Moving Object; Spatio-Temporal Data Mining; Pattern Mining; Optimal Path Search;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 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,” proc. on International Conference on Computational Science and Its Applications(ICCSA), pp.259-269, 2006   DOI   ScienceOn
2 J. W. Lee, O. H. Paek and K. H. Ryu, “Temporal Moving Pattern Mining for Location-Based Service,” The Journal of Systems and Software, Vol.73, 2004   DOI   ScienceOn
3 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
4 Y. Huang, L. Zhang and P. Zhang, “Finding Sequential Patterns from a Massive Number of Spatio-Temporal Events,” SDM, SIAM, 2006
5 G. Yavas, D. Katsaros, O. Ulusoy and Y. Manolopoulos, “A Data Mining Approach for Location Prediction in Mobile Environmensts,” Data & Knowledge Engineering, Vol.54, pp.121-146, 2005   DOI   ScienceOn
6 Y. Wnag, E. P. Lim and S. Y. Hwang, “On Mining Group Patterns of Mobile Users,” DEXA, Lecture Notes in Computer Science, Springer, Vol.2736, pp.287-296, 2003   DOI   ScienceOn
7 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   DOI
8 이준욱, “지식 탐사 프레임워크 기반의 시공간 이동 패턴 탐사 기법”, 충북대학교 대학원, 박사학위논문, 2003
9 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   DOI
10 백옥현, “위치 기반 서비스를 위한 이동 객체의 시간 패턴 탐사 기법”, 충북대학교 대학원, 석사학위논문, 2002
11 한선영, “시공간 이동 시퀀스 패턴 마이닝 기법”, 이화여자대학교 대학원, 석사학위논문, 2006
12 고현, 김광종, 이연식, “$R^*$-Tree와 Grid를 이용한 이동 객체의 위치 일반화 기법”, 한국컴퓨터정보학회 논문지, Vol. 12, No.2, pp.231-242, 2007
13 P. Laube and S. Imfeld, “Analyzing Relative Motion within Groups of Trackable Moving Point Object,” in GIScience, Notes in Computer Science, Springer, Vol.2478, pp.132-144, 2002   DOI   ScienceOn
14 S. Y. Hawng, Y. H. Liu, J. K. Chiu and E. P. Lim, “Mining Mobile Group Patterns : A Trajectory-based Approach,” PAKDD, Lecture Notes in Computer Science, Springer, Vol.3518, pp.713-718, 2005   DOI   ScienceOn
15 이준욱, “위치 기반 서비스를 위한 이동 객체의 시간 패턴 탐사”, 한국정보과학회 논문지, 제29권, 제5호, 2002   과학기술학회마을
16 박지웅, “시공간 이동 패턴 추출을 위한 효율적인 알고리즘”, 건국대학교 대학원, 박사학위논문, 2006