Fuzzy association rule mining for community crime pattern discovery

Proceedings of the ACM SIGKDD Workshop on Intelligence and Security Informatics 2010, ISI-KDD 2010

Volumn , Issue , 2010, Pages

  Buczak, Anna L ^a   Gifford, Christopher M ^a  

^a JOHNS HOPKINS UNIVERSITY APPLIED PHYSICS LABORATORY   (United States)

Author keywords

Community based crime; Crime data mining; Fuzzy association rules; Rule pruning

Indexed keywords

COMMUNITY-BASED CRIME; COMPLEX RELATIONSHIPS; CRIME DATA; CRIME DATA MINING; FUZZY ASSOCIATION RULE; FUZZY ASSOCIATION RULES; KNOWLEDGE DISCOVERY; LAW ENFORCEMENT PERSONNEL; MANUAL INSPECTION; NATIONAL LEVEL; PATTERN DISCOVERY; RULE PRUNING; TIME FRAME;

ASSOCIATION RULES; DATA MINING; FUZZY RULES; INFORMATION SCIENCE;

CRIME;

EID: 79952519231     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1938606.1938608     Document Type: Conference Paper

References (21)

1. R. Agrawal, T. Imielinski, and A. Swami, "Mining Association Rules between Sets of Items in Large Databases," In Proceedings of the International Conference on Management of Data, Washington, D.C., pp. 207-216, May 1993.
2. A. Asuncion and D.J. Newman, "UCI Machine Learning Repository," School of Information and Computer Science, University of California, Irvine, CA, 2007, URL: archive.ics.uci.edu/ml/datasets/Communities+and+Crime.
3. S. Bagui, "An Approach to Mining Crime Patterns," International Journal of Data Warehousing and Mining, 2(1), pp. 50-80, March 2006.
4. R.J. Bayardo, R. Agrawal, and D. Gunopulos, "Constraint-Based Rule Mining in Large, Dense Databases," Data Mining and Knowledge Discovery, 4(2/3), pp. 217-240, 2000.
5. D. Brown, "The Regional Crime Analysis Program (RECAP): A Framework for Mining Data to Catch Criminals," In Proceedings of the International Conference on Systems, Man, and Cybernetics, pp. 2848-2853, 1998.
6. J. de Bruin, T. Cocx, W. Kosters, J. Laros, and J. Kok, "Data Mining Approaches to Criminal Career Analysis," In Proceedings of the International Conference on Data Mining, pp. 171-177, 2006, Washington, D.C., IEEE Computer Society Press.
7. M. Chau, J. Xu, and H. Chen, "Extracting Meaningful Entities from Police Narrative Reports," In Proceedings of the National Conference on Digital Government Research, pp. 1-5, 2002.
8. H. Chen, W. Chung, J. Xu, G. Wang, Y. Qin, and M. Chau, "Crime Data Mining: A General Framework and Some Examples," Computer, 37(4), pp. 50-56, April 2004, Los Alamitos, CA, IEEE Computer Society Press.
9. J. Dembsky, "United States Regions," Online. Available (October 2006): http://www.dembsky.net/regions/.
10. R. Hauck, H. Atabakhsh, P. Ongvasith, H. Gupta, and H. Chen, "Using COPLINK to Analyze Criminal-Justice Data," Computer, 35(3), pp. 30-37, March 2002, Los Alamitos, CA. (Pubitemid 34254680)
11. C. Ku, A. Iriberri, and G. Leroy, "Crime Information Extraction from Police and Witness Narrative Reports," In Proceedings of the IEEE International Conference on Technologies for Homeland Security, pp. 193-198, May 2008, Boston, MA.
12. C.M. Kuok, A. Fu, and M.H. Wong, "Mining Fuzzy Association Rules in Databases," ACM SIGMOD Record, 27(1), pp. 41-46, New York, NY, 1998. (Pubitemid 128456025)
13. B. Liu, W. Hsu, and Y. Ma, "Mining association rules with multiple minimum supports," In Proceedings of the International Conference on Knowledge Discovery and Data Mining, pp. 337-341, New York, NY, 1999.
14. S. Nath, "Crime Pattern Detection Using Data Mining," In Proceedings of the International Conference on Web Intelligence and Intelligent Agent Technology, pp. 41-44, 2006, Washington, D.C., IEEE Computer Society Press.
15. V. Ng, S. Chan, D. Lau, and C. Ying, "Incremental Mining for Temporal Association Rules for Crime Pattern Discoveries," In Proceedings of the Australasian Database Conference, pp. 123-132, Ballarat, Victoria, Australia, February 2007.
16. P. Phillips and I. Lee, "Mining Top-k and Bottom-k Correlative Crime Patterns through Graph Representations," In Proceedings of the IEEE International Conference on Intelligence and Security Informatics, pp. 25-30, June 2009, Dallas, TX.
17. M.A. Redmond, and A. Baveja, "A Data-Driven Software Tool for Enabling Cooperative Information Sharing Among Police Departments," European Journal of Operational Research, 141, pp. 660-678, 2002.
18. R. Srikant and R. Agrawal, "Mining Quantitative Association Rules in Large Relational Tables," In Proceedings of the International Conference on Management of Data, Montreal, Quebec, Canada, pp.1-12, 1996. (Pubitemid 126440751)
19. P. Thongtae and S. Srisuk, "An Analysis of Data Mining Applications in Crime Domain," In Proceedings of the IEEE International Conference on Computer and Information Technology Workshops, pp. 122-126, 2006, IEEE Computer Society Press.
20. H. Yun, D. Ha, B. Hwang, and K.H. Ryu, "Mining Association Rules on Significant Rare Data using Relative Support," Journal of Systems and Software, 67(3), pp. 181-191, 2003.
21. L.A. Zadeh, "Fuzzy Sets," Information and Control, 8(3), pp. 338-353, 1965.