Discovering and explaining abnormal nodes in semantic graphs

IEEE Transactions on Knowledge and Data Engineering

Volumn 20, Issue 8, 2008, Pages 1039-1052

  Lin, Shou De ^a   Chalupsky, Hans ^b  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Anomaly detection; Data mining; Knowledge and data engineering tools and techniques; Semantic graphs

Indexed keywords

(E ,3E) PROCESS; CENTRAL NODES; COMPLEX DATA; DIFFERENT TYPES; EXPLANATION SYSTEMS; GRAPH-BASED; HOMELAND SECURITY (HLS); HUMAN SUBJECTS; LARGE DATA SETS; NATURAL LANGUAGE EXPLANATIONS; NUMERICAL DATA; OUTLIER DETECTION; SEMANTIC GRAPHS; SOCIAL NETWORK ANALYSIS (SNA); UNSUPERVISED NETWORK;

ADMINISTRATIVE DATA PROCESSING; ARTS COMPUTING; DECISION SUPPORT SYSTEMS; ELECTRIC NETWORK ANALYSIS; GRAPH THEORY; INFORMATION MANAGEMENT; INFORMATION THEORY; KNOWLEDGE MANAGEMENT; ONLINE SEARCHING; SEARCH ENGINES; SEMANTICS; SET THEORY; STATISTICAL METHODS;

SECURITY OF DATA;

EID: 46649095259     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2007.190691     Document Type: Conference Paper

References (39)

1. M. Sparrow, "The Application of Network Analysis to Criminal Intelligence: An Assessment of the Prospects," Social Networks, vol. 13, pp. 251-274, 1991.
2. T. Senator and H. Goldberg, "Break Detection Systems," Handbook of Knowledge Discovery and Data Mining, W. Kloesgen and J. Zytkow, eds., pp. 863-873, Oxford Univ. Press, 2002.
3. D. Jensen, M. Rattigan, and H. Blau, "Information Awareness: A Prospective Technical Assessment," Proc. Ninth ACM SIGKDD Int'l Conf Knowledge Discovery and Data Mining (KDD '03), pp. 378-387, 2003.
4. J. Wang, F. Wang, and D. Zeng, "Rule+Exception Learning-Based Class Specification and Labeling in Intelligence and Security Analysis," Proc. Workshop Intelligence and Security Informatics (WISI '06), vol. 3917, pp. 181-182, 2006.
5. V. Krebs, "Mapping Networks of Terrorist Cells," Connections, vol. 24, no. 3, pp. 43-52, 2001.
6. J. Qin, J. Xu, D. Hu, M. Sageman, and H. Chen, "Analyzing Terrorist Networks: A Case Study of the Global Salafi Jihad Network," Intelligence and Security Informatics, P. Kantor et al., ed., pp. 287-304, Springer, 2005.
7. "Total Information Overload," Scientific Am., editorial, Mar. 2003.
8. B. Simons and E. Spafford, Letter from tlte Association for Computing Machinery's US Public Policy Committee to the Senate Armed Services Committee, Jan. 2003.
9. R. Hill, "Non-Well-Founded Set Theory and the Circular Semantics of Semantic Networks," Intelligent Systems: Third Golden West International Conference: Edited and Selected Papers, E. Yfantis, ed., pp. 375-386, Kluwer, 1995.
10. S. Lin, "Modeling, Finding, and Explaining Abnormal Instances in Multi-Relational Networks," PhD dissertation, Dept. of Computer Science, Univ. of Southern California, 2006.
11. S. Ramaswamy, R. Rastogi, and K. Shim, "Efficient Algorithms for Mining Outliers from Large Data Sets," Proc. ACM SIGMOD '00, pp. 427-438, 2000.
12. S. Lin and H. Chalupsky, "Issues of Verification for Unsupervised Discovery Systems," Proc. Workshop Link Analysis and Group Detection (LinkKDD '04), 2004.
13. R. Schrag, "A Performance Evaluation Laboratory for Automated Threat Detection Technologies," Proc. Performance Measures for Intelligent Systems Workshop (PerMIS '06), 2006.
14. L. Page, S. Brin, R. Motwani, and T. Winograd, "The PageRank Citation Ranking: Bringing Order to the Web," Proc. Seventh Int'l World Wide Web Conf. (WWW '98), pp. 161-172, 1998.
15. J. Kleinberg, "Authoritative Sources in a Hyperlinked Environment," J. ACM, vol. 46, no. 5, pp. 604-632, 1999.
16. S. Wasserman and K. Faust, Social Network Analysis: Methods and Applications. Cambridge Univ. Press, 1994.
17. S. Dongen, "A Cluster Algorithm for Graphs," Technical Report INS-R0010, Nat'l Research Inst. for Math. and Computer Science, Amsterdam, The Netherlands, 2000.
18. J. Adibi, H. Chalupsky, E. Melz, and A. Valente, "The KOJAK Group Finder: Connecting the Dots via Integrated Knowledge-Based and Statistical Reasoning," Proc. 16th Innovative Applications of Artificial Intelligence Conf. (IAAI '04), pp. 800-807, 2004.
19. S. Lin, "Generating Natural Language Descriptions for Paths in the Semantic Network," final project report, Dept. of Linguistics, Univ. of Southern California, 2006.
20. R. Popp, "Countering Terrorism through Information Technology," Comm. ACM, vol. 47, no. 3, pp. 36-43, 2004.
21. H. Chen and F. Wang, "Artificial Intelligence for Homeland Security," IEEE Intelligent Systems, vol. 20, no. 5, pp. 12-16, 2005.
22. J. Xu and H. Chen, "Criminal Network Analysis and Visualization," Comm. ACM, vol. 48, no. 6, pp. 101-107, 2005.
23. H. Chen and J. Xu, "Intelligence and Security Informatics for National Security: A Knowledge Discovery Perspective," Ann. Rev. of Information Science and Technology, vol. 40, pp. 229-289, 2006.
24. B. Taskar, M.-F. Wong, P. Abbeel, and D. Koller, "Link Prediction in Relational Data," Advances Neural Information Processing Systems - Proc. 17th Ann. Conf Neural Information Processing Systems (NIPS '03), 2004.
25. S. Adafre and M. Rijke, "Discovering Missing Links in Wikipedia," Proc. Workshop Link Discovery: Issues, Approaches and Applications (LinkKDD '05), 2005.
26. R. Bunescu and R. Mooney, "Relational Markov Networks for Collective Information Extraction," Proc. 21st Int'l Conf Machine Learning (ICML '04), 2004.
27. J. Neville and D. Jensen, "Dependency Networks for Relational Data," Proc. Fourth IEEE Infi Conf Data Mining (ICDM '04), 2004.
28. M. Jaeger, "Relational Bayesian Networks," Proc. 13th Ann. Conf Uncertainty in Artificial intelligence (UAl '97), 1997.
29. S. Lin and H. Chalupsky, "Unsupervised Link Discovery in Multi-Relational Data via Rarity Analysis," Proc. Third IEEE Int'l Conf Data Mining (ICDM '03), pp. 171-178, 2003.
30. S. Lin and H. Chalupsky, "Using Unsupervised Link Discovery Methods to Find Interesting Facts and Connections in a Bibliography Dataset," SIGKDD Explorations, vol. 5, no. 2, pp. 173-178, Dec. 2003.
31. S. Dzeroski, "Data Mining in a Nutshell," Relational Data Mining, S. Dzeroski and N. Lavrac, eds. pp. 1-27, Springer, 2001.
32. K. Morik, "Detecting Interesting Instances," Proc. ESF Exploratory Workshop Pattern Detection and Discovery, 2002.
33. F. Angiulli, R. Ben-Eliyahu-Zohary, and L. Palopoli, "Outlier Detection Using Default Logic," Proc. 18th Int'l Joint Conf. Artificial intelligence (IJCAI '03), pp. 833-838, 2003.
34. P. Flach and N. Lachiche, "Confirmation-Guided Discovery of First-Order Rules with Tertius," Machine Learning, vol. 42, nos. 1-2, pp. 61-95, 2001.
35. S. Wrobel, "An Algorithm for Multi-Relational Discovery of Subgroups," Proc. First European Symp. Principles of Data Mining and Knowledge Discovery (PKDD '97), pp. 78-87, 1997.
36. W. Klosgen, "Explora: A Multipattern and Multistrategy Discovery Assistant," Advances in Knowledge Discovery and Data Mining, U. Fayyad et al., ed., pp. 249-271, AAAI/MIT Press, 1996.
37. K. Yamanishi and J. Takeuchi, "Discovering Outlier Filtering Rules from Unlabeled Data: Combining a Supervised Learner with an Unsupervised Learner," Proc. Seventh ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '01), pp. 389-394, 2001.
38. Y. Yao, Y. Zhao, and R. Maguire, "Explanation-Oriented Association Mining Using a Combination of Unsupervised and Super-vised Learning Algorithms," Proc. Canadian Conf. Artificial intelligence, pp. 527-531, 2003.
39. Y. Yao, Y. Zhao, and R. Maguire, "Explanation Oriented Association Mining Using Rough Set Theory," Proc. Ninth Int'l Conf Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing (RSFDGrC '03), pp. 165-172, 2003.