TrajPattern: Mining sequential patterns from imprecise trajectories of mobile objects

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3896 LNCS, Issue , 2006, Pages 664-681

  Yang, Jiong ^a   Hu, Meng ^a  

^a CASE WESTERN RESERVE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CELLULAR TELEPHONE SYSTEMS; DATA MINING; MOBILE TELECOMMUNICATION SYSTEMS; SENSORS; TELECOMMUNICATION NETWORKS;

MOBILE COMMUNICATION NETWORKS; SCALABILITY; SEQUENTIAL PATTERN MODELS; TRAJPATTERN ALGORITHM;

OBJECT RECOGNITION;

EID: 33745595860     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11687238_40     Document Type: Conference Paper

References (17)

1. J. Han, G. Dong, and Y. Yin. Efficient mining partial periodic patterns in time series database. Proc. of ICDE, 1999.
2. A. Jain, E. Chang, Y. Wang. Adaptive stream resource management using Kalman filters. Proc. of SIGMOD, 2004.
3. Y. Li, J. Han, and J. Yang. Clustering mobile objects. Proc. of KDD, 2004.
4. N. Mamoulis, H. Cao, G. Kollios, M. Hadjieleftheriou, Y. Tao, D. Cheung. Mining, indexing, and querying historical spatiotemporal data. Proc. of KDD, 2004.
5. W.-C. Peng and M.-S. Chen. Developing data allocation schemes by incremental mining of user moving patterns in a mobile computing system. IEEE TKDE, 2003.
6. Song, Z., Roussopoulos, N. K-Nearest neighbor search for moving query point. SSTD, 2001.
7. J. Patel, Y. Chen, V. Chakka STRIPES: an efficient index for predicted trajectories. In Proc. of SIGMOD, 2004.
8. J. Pei, J. Han, H. Pinto, Q. Chen, U. Dayal, and M. Hsu. PrefixSpan: mining sequential patterns efficiently by prefix-projected pattern growth. Proc. of ICDE, 2001.
9. S. Saltenis, C.S. Jensen, S.T. Leutenegger, and M.A. Lopez. Indexing the positions of continuously moving objects, In Proc. of SIGMOD, 2000.
10. Y. Tao, J. Sun, and D. Papadias. Selectivity estimation for predictive spatio-temporal queries. In Proc. of ICDE, pp. 417-428, Bangalore, India, Mar. 2003.
11. Y. Tao, C. Faloutsos, and D. Papadias. Prediction and indexing of moving objects with unknown motion patterns. In Proc. of SIGMOD, 2004.
12. O. Wolfson, P. Sistla, S. Chamberlain, and Y. Yesha. Updating and query databases that track mobile unites. Distributed and Parallel Databases, 7(3), 1999.
13. J. Yang, W. Wang, and P. Yu. Infominer: mining surprising periodic patterns. Proc. of (KDD). pp. 395-400, 2001.
14. J. Yang, W. Wang, P. Yu, and J. Han. Mining long sequential patterns in a noisy environment. Proc. of SIGMOD, 2002.
15. M. Zaki. SPADE: an efficient algorithm for mining frequent sequences. Machine Learning, 42(1/2):31-60, 2001.
16. Y. Wang, M. Martonosi, L.S. Peh, P. Zhang, C. Sadler, T. Liu, D. Rubenstein, S.A. Lyon. ZebraNet mobility data, unpublished, Princeton University 2004
17. J. Yang and M. Hu. TrajPattern: Mining sequential patterns from imprecise trajectories of mobile objects. Technical Report, EECS, Case Western Reserve University, 2005