Spatial movement pattern discovery with LCS-based path similarity measure

15th Americas Conference on Information Systems 2009, AMCIS 2009

Volumn 1, Issue , 2009, Pages 394-401

  Yan, Ping ^a   Zeng, Daniel D ^a,b  

^a UNIVERSITY OF ARIZONA   (United States)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Clustering; LCS algorithm; Movement tracking; Pattern discovery; Ubiquitous computing

Indexed keywords

ATHENS , GREECE; CLUSTERING; CLUSTERING RESULTS; DATA SETS; EUCLIDEAN SPACES; EVALUATION RESULTS; LOCATION-ENHANCED; LONGEST COMMON SUBSEQUENCES; MASS ADOPTION; MOVEMENT PATTERN; MOVEMENT TRAJECTORIES; MOVING OBJECTS; ORIENTATION SENSORS; PATTERN DISCOVERY; RF-ID TAGS; SEQUENTIAL PATTERNS; SIMILARITY MEASURE; SPATIAL DATA MINING; TRAVEL PATTERNS; TRAVEL ROUTES;

INFORMATION SYSTEMS; MINING; TRAJECTORIES; UBIQUITOUS COMPUTING;

CLUSTERING ALGORITHMS;

EID: 84870263788     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (36)

1. Berkhin, P., (2002) Survey of Clustering Data Mining Techniques.
2. Bergroth, L., Hakonen, H., and Raita, T. (2000) A Survey of Longest Common Subsequence Algorithms, Proceedings of Seventh International Symposium on String Processing and Information Retrieval (SPIRE), 39-48.
3. Dey, A. (2001) Understanding and Using Context. Personal and Ubiquitous Computing, 5, 1, 4-7.
4. Ekbia, Hamid, (2007) Mediated Interaction: Social Informatics in the Era of Ubiquitous Computing, Proceedings of the 13th Americas Conference on Information systems (AMCIS 2007). August, Keystone, Colorado.
5. Finkenzeller, K. (2002) RFID Handbook (second edition), Wiley & Sons.
6. Gaffney, S. and Smyth, P. (1999) Trajectory Clustering with Mixtures of Regression Models, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, ACM Press, 63-72
7. Giannotti, F., Nanni, M., Pinelli, F., et al. (2007) Trajectory Pattern Mining, Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '07), 330-339.
8. Google, KML Documentation Introduction: http://code.google.com/apis/kml/documentation/.
9. Hans van der Heijden (2006) Mobile Decision Support for In-store Purchase Decisions, Decision Support Systems, 42, 656-663.
10. Jain, A. K., Murty, M. N., and Flynn, P. J. (1999) Data clustering: a review, ACM Computing Surveys, 31, 3, 264-323.
11. Jorns, O. and Quirchmayr, G., (2008) Cross Domain Privacy Protection for Location-Based Services, Proceedings of the 14th Americas Conference on Information systems (AMCIS 2008). August, Toronto, Ontario
12. Kalnis, P., Mamoulis, N., and Bakiras, S. (2005) On Discovering Moving Clusters in Spatio-temporal Data, Proceedings of the 9th International Symposium on Spatial and Temporal Databases, Springer.
13. Karypis, G., (2002) CLUTO: Software package for clustering high dimensional data. http://www.cs.umn.edu/~karypis/cluto
14. Kleinberg, J. (2002) An Impossibility Theorem for Clustering, Proceedings of the 15th Conference on Neural Information Processing Systems (NIPS), Vancouver, Canada.
15. Kourouthanassis, P. and Roussos, G. (2003) Developing Consumer-Friendly Pervasive Retail Systems, IEEE Pervasive Computing, 2, 2, 32-39.
16. Li, L., Fox, D., and Kautz, H. (2007) Learning and inferring transportation routines, Artificial Intelligence, 171, 5, 311-331.
17. Li, X., Han, J., Kim, S. and Gonzalez, H. (2007) ROAM: Rule-and Motif-Based Anomaly Detection in Massive Moving Object Data Sets, Proceedings of International Conference on Data Mining (SDM07), Minneapolis, MN.
18. Li, T., Ma, S., and Ogihara, M., (2004) Entropy-based criterion in categorical clustering, Proceedings of the twenty-first international conference on Machine learning (ICML '04), 536-543.
19. Loebbecke, C., Fujita, M., and Huyskens, C. (2007) Towards Item-Level RFID in the Japanese Publishing Industry, Proceedings of the 13th Americas Conference on Information systems (AMCIS 2007). August, Keystone, Colorado
20. Masciari, E. (2007) RFID data management for effective objects tracking. Proceedings of the 2007 ACM Symposium on Applied Computing (SAC '07), Seoul, Korea, March, ACM, New York, NY, 457-461.
21. Resatsch, F., Sandner, U., Michelis, D., Hoechst, C., and Schildhauer, T. (2007) Everyday Simplicity: The Implications of Everyday Tasks for Ubiquitous Computing Applications, Proceedings of the 13th Americas Conference on Information systems (AMCIS 2007). August, Keystone, Colorado.
22. Scherner, Tobias, (2007) Enabling Efficient and Privacy-friendly Location-based Services with Standardized Intermediary Infrastructures, Proceedings of the 13th Americas Conference on Information systems (AMCIS 2007). August, Keystone, Colorado.
23. Shim, J. P. (2006) Mobile Wireless Services and Technologies in Ubiquitous and Embedded Computing: Trends, Proceedings of the 12th Americas Conference on Information systems (AMCIS 2006), August, Acapulco, México.
24. Sparacino, F. (2002) The museum wearable: Real-time sensor-driven understanding of visitors' interests for personalized visually-augmented museum experiences, Proceedings of the Museums and the Web, Boston, MA.
25. Spatio-temporal (trajectory) datasets. 2006: http://www.rtreeportal.org/
26. Snay, R. A. and Soler, T. (2000) Modern Terrestrial Reference Systems, PART 3: WGS 84 and ITRS. http://www.ngs.noaa.gov/CORS/Articles/Reference-Systems-Part-3.pdf.
27. Stahl, F. and Freudenschuss, M. (2006) Mobile Business Through RFID Technology: About The Potential Of RFID Technology For Distributing Free And Paid Content On Mobile Devices In Retail Business, Proceedings of the 12th Americas Conference on Information systems (AMCIS 2006), August, Acapulco, México.
28. Tewary, A., Kosalge, P., and Motwani, J. (2008) Piloting RFID in an Aerospace and Defense Supply Chain, Proceedings of the 14th Americas Conference on Information systems (AMCIS 2008). August, Toronto, Ontario.
29. Thiesse, F., Fleisch, E., Sorensen, C. and Tellkamp, C. (2007) RFID-Enabled Shelf Replenishment with Case-Level Tagging: A Simulation Study, Proceedings of the 13th Americas Conference on Information systems (AMCIS 2007). August, Keystone, Colorado
30. Tung, A.K.H., Hou, J., and Han, J. (2000) COE: Clustering with Obstacles Entities. A Preliminary Study, Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications (PADKK '00), 165-168.
31. Tung, A.K.H., Hou, J., and Han, J. (2001) Spatial Clustering in the Presence of Obstacles, Proceedings of the 17th International Conference on Data Engineering, 359-367.
32. Vlachos, M., Kollios, G. and Gunopulos, D. (2002) Discovering similar multidimensional trajectories, Proceedings of the 16th International Conference on Data Engineering (ICDE '02).
33. Wedel, M., and Kamakura, W. (2000) Market Segmentation: Conceptual and Methodological Foundations (2nd ed.), Kluwer Academic Publishers, Norwell, Massachusetts
34. Wolf, J., Guensler, R., and Bachman, W. (2001) Elimination of the travel diary: An experiment to derive trip purpose from GPS travel data, Notes from Transportation Research Board, 80th annual meeting, Washington, D.C.
35. Yan, P. and Zeng, D. (2008) Clustering Customer Shopping Trips with Network Structure, Proceedings of the International Conference on Information Systems (ICIS 2008), December, Paris, France.
36. Zhou, C., Terveen, L., and Shekhar, S. (2005) Discovering Personal Paths from Sparse GPS Traces, Proceedings of the JCIS 2005 Workshop on Data Mining, 266-273.