Cascading spatio-temporal pattern discovery: A summary of results

Proceedings of the 10th SIAM International Conference on Data Mining, SDM 2010

Volumn , Issue , 2010, Pages 327-338

  Mohan, Pradeep ^a   Shekhar, Shashi ^a   Shine, James A ^b   Rogers, James P ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b Office Asst Sec Defense Research and Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMOBILE DRIVERS; CRIME; DISASTER PREVENTION; DISASTERS; LARGE DATASET;

CANDIDATE PATTERNS; COMPUTATIONAL COSTS; COMPUTATIONALLY EFFICIENT; FILTERING STRATEGIES; NATURAL DISASTERS; NOVEL ALGORITHM; PARTICIPATION INDEX; SPATIOTEMPORAL PATTERNS;

DATA MINING;

EID: 84866606114     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972801.29     Document Type: Conference Paper

References (29)

1. Committee on Strategic Advice on the U.S. Climate Change Science Program; National Research Council: Restructuring Federal Climate Research to Meet the Challenges of Climate Change. The National Academies Press, Washington D.C., 2009.
2. R. Agrawal, D. Gunopulos, and F. Leymann. Mining process models from workflow logs. In Sixth International Conference on Extending Database Technology, pages 469-483, 1998.
3. R. Agrawal, T. Imielinski, and A. N. Swami. Mining association rules between sets of items in large databases. In SIGMOD Conference, pages 207-216, 1993.
4. J. F. Allen. Maintaining knowledge about temporal intervals. Comm. of the ACM, 26(11):832-843, 1983.
5. J. F. Allen. Towards a general theory of action and time. Artif. Intell., 23(2):123-154, 1984.
6. M. Celik, S. Shekhar, J. P. Rogers, and J. A. Shine. Mixed-drove spatiotemporal co-occurrence pattern mining. IEEE Transactions on Knowledge and Data Engineering, 20(10):1322-1335, 2008.
7. A. Cliff, P. Haggett, J. K. Ord, and G. Versey. Spatial Diffusion: An Historical Geography of Epidemics in an Island Community. Cambridge University Press, Cambridge, 1981.
8. L. C. P. Department. Lincoln city crime records. http://www.lincoln.ne. gov/city/police/, 2008.
9. E. Gabriel and P.J. Diggle. Second-order analysis of inhomogeneous spatio-temporal point process data. Statistica Neerlandica, 63(1):43-51, January 2009.
10. M. Fujita, P. Krugman, and A. Venables. The spatial economy: cities, regions and international trade. The MIT press, 2001.
11. A. Galton. Towards a qualitative theory of movement. In Int. Conf. on Spatial Information Theory, LNCS 988, pages 377-396. Springer, 1995.
12. M. R. Garey and D. S. Johnson. Computers and Intractability: A guide to the theory of NP-Completeness. W.H. Freeman and Company, New York, USA, 1979.
13. Y. Huang, L. Zhang, and P. Zhang. A framework for mining sequential patterns from spatio-temporal event data sets. IEEE Transactions on Knowledge and Data Engineering, 20(4):433-448, 2008.
14. M. Kuramochi and G. Karypis. An efficient algorithm for discovering frequent subgraphs. IEEE Transactions on Knowledge and Data Engineering, 16(9):1038-1051, Sept. 2004.
15. M. Kuramochi and G. Karypis. Finding frequent patterns in a large sparse graph. Data Mining and Knowledge Discovery, 11(3):243-271, 2005.
16. F. Massey Jr. The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association, pages 68-78, 1951.
17. P. Mohan, S. Shekhar, J. A. Shine, and J. P. Rogers. Cascading spatio-temporal pattern discovery: A summary of results. Technical Report TR10-001, Department of Computer Science and Engineering, University of Minnesota, 2010.
18. D. M. Morens, G. K. Folkers, and A. S. Fauci. The challenge of emerging and re-emerging infectious diseases. Nature, 430:242-249, July 2004.
19. J. Pearl and G. Shafer. Probabilistic reasoning in intelligent systems: networks of plausible inference. JSTOR, 1988.
20. J. Pei, J. Liu, K. Wang, et al Discovering frequent closed partial orders from strings. IEEE Transactions on Knowledge and Data Engineering, 18(11):1481, 2006.
21. P.J. Diggle, A. G. Chetwynd, R. Haggkvist, and S. Morris. Second-order analysis of space-time clustering. Stat. Methods in Med. Res., 4:124-136, 1995.
22. R. Robinson. Counting labeled acyclic digraphs. New directions in the theory of graphs, pages 239-273, 1973.
23. S. Shekhar and Y. Huang. Discovering spatial co-location patterns: A summary of results. In Lecture Notes in Computer Science, pages 236-256, 2001.
24. S. Shekhar and H. Xiong, editors. Encyclopedia of GIS. Springer, 2008.
25. R. Srikant, R. Srikant, R. Agrawal, and R. Agrawal. Mining sequential patterns: Generalizations and performance improvements. pages 3-17, 1996.
26. M. S. Scott and K. Dedel. Assaults in and around bars(2nd edition). Problem Oriented Guides for Police, Problem Specific Guides, 1:1-78, 2006.
27. A. M. Turing. The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London Series B, 237:37-72, 1952.
28. J. Wang, W. Hsu, and M. L. Lee. A framework for mining topological patterns in spatio-temporal databases. In CIKM '05: Proc. of the 14th ACM int'l conf. on Information and knowledge management, pages 429-436, NY, USA, 2005. ACM.
29. M. F. Worboys. Event-oriented approaches to geographic phenomena. International Journal of Geographical Information Science, 19(1):1-28, 2005.