Trajectory pattern mining

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2007, Pages 330-339

  Giannotti, Fosca ^a   Nanni, Mirco ^a   Pinelli, Fabio ^b   Pedreschi, Dino ^a  

^a ISTI CNR   (Italy)

^b UNIVERSITY OF PISA   (Italy)

Author keywords

Spatio temporal data mining; Trajectory patterns

Indexed keywords

COMPUTATIONAL COMPLEXITY; DATABASE SYSTEMS; GLOBAL POSITIONING SYSTEM; GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS; PATTERN RECOGNITION; PROBLEM SOLVING;

SPATIO-TEMPORAL DATA MINING; TRAJECTORY PATTERNS;

DATA MINING;

EID: 36849001879     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1281192.1281230     Document Type: Conference Paper

References (12)

1. R. Agrawal and R. Srikant. Mining sequential patterns. In Proceedings of ICDE, 1995.
2. K. Ashok. Estimation and Prediction of Time-Dependent Origin-Destination Flows. PhD thesis, Massachusetts Institute of Technology, 1996.
3. H. Cao, N. Mamoulis, and D. W. Cheung. Mining frequent spatio-temporal sequential patterns. In ICDM, 2005.
4. F. Giannotti, A. Mazzoni, S. Puntoni, and C. Renso. Synthetic generation of cellular network positioning data. In GIS '05: Procs of 13th ACM Int. Workshop on Geographic Information Systems, pages 12-20, New York, NY, USA, 2005. ACM Press.
5. F. Giannotti, M. Nanni, and D. Pedreschi. Efficient mining of sequences with temporal annotations. In roc. SIAM Conference on Data Mining, pages 346-357. SIAM, 2006.
6. F. Giannotti, M. Nanni, F. Pinelli, and D. Pedreschi. T-patterns: temporally annotated sequential patterns over trajectories. Technical report, ISTI-CNR, 2006.
7. P. Kalnis, N. Mamoulis, and S. Bakiras. On discovering moving clusters in spatio-temporal data. In Proceedings of 9th International Symposium on Spatial and Temporal Databases, pages 364-381. Springer, 2005.
8. N. Mamoulis, H. Cao, G. Kollios, M. Hadjieleftheriou, Y. Tao, and D. W. Cheung. Mining, indexing, and querying historical spatiotemporal data. In KDD, 2004.
9. J. Pei et al. Prefixspan: Mining sequential patterns by prefix-projected growth. In ICDE, pages 215-225, 2001.
10. A. Vautier, M.-O. Cordier, and R. Quiniou. An inductive database for mining temporal patterns in event sequences. In Proceedings of the workshop on Mining Spatial and Temporal Data, 2000.
11. M. Yoshida et al. Mining sequential patterns including time intervals. In Data Mining and Knowledge Discovery: Theory, Tools and Technology II (SPIE Conference), 2000.
12. M. J. Zaki. Spade: An efficient algorithm for mining frequent sequences. Machine Learning, 42(1/2):31-60, 2001.