A fuzzy graph matching approach in intelligence analysis and maintenance of continuous situational awareness

Information Fusion

Volumn 18, Issue 1, 2014, Pages 43-61

  Gross, Geoff ^a   Nagi, Rakesh ^a   Sambhoos, Kedar ^a  

^a State University of New York   (United States)

Author keywords

Fuzzy systems; Graph matching; Incremental graph matching; Situational awareness; Stochastic graphical methods

Indexed keywords

COGNITIVE LIMITATIONS; GRAPH MATCHINGS; GRAPHICAL METHODS; INTELLIGENCE ANALYSTS; MAINTENANCE ALGORITHMS; PRIORITY INFORMATION REQUESTS; SITUATIONAL AWARENESS; UNCERTAINTY REPRESENTATION;

ALGORITHMS; ALIGNMENT; FUZZY SETS; FUZZY SYSTEMS; MAINTENANCE; SENSORS; STOCHASTIC SYSTEMS;

PATTERN MATCHING;

EID: 84892364695     PISSN: 15662535     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.inffus.2013.05.006     Document Type: Article

References (57)

1. W.C. Elm, M.J. Cook, F.L. Greitzer, R.R. Hoffman, B. Moon, S.G. Hutchins, Designing support for intelligence analysis, in: Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting, New Orleans, LA, 2004.
2. R.J. Heuer, Psychology of Intelligence Analysis, C. f. t. S. o. Intelligence, Washington, DC, 1999.
3. J. Llinas, D.L. Hall, An introduction to multi-sensor data fusion, in: 1998 IEEE International Symposium on Circuits and Systems, 1998.
4. M. Prentice, M. Kandefer, S.C. Shapiro, Tractor: a framework for soft information fusion, in: 13th International Conference on Information Fusion, Edinburgh, UK, 2010.
5. M. Prentice, S.C. Shapiro, Using propositional graphs for soft information fusion, in: Presented at the 14th International Conference on Information Fusion, Chicago, IL, 2011.
6. M. Kandefer, S.C. Shapiro, Evaluating spreading activation for soft information fusion, in: Presented at the 14th International Conference on Information Fusion, Chicago, IL, 2011.
7. J.C. Helton, J.D. Johnson, W.L. Oberkampf, and C.J. Sallaberry Representation of Analysis Results Involving Aleatory and Epistemic Uncertainty 2008 Sandia Corporation Albuquerque
8. N. Cantor, E.E. Smith, R.D. French, and J. Mezzich Psychiatric diagnosis as prototype categorization Journal of Abnormal Psychology 89 2 1980 181 193 (Pubitemid 10091844)
9. L.A. Zadeh Fuzzy sets as a basis for a theory of possibility Fuzzy Sets and Systems 100 1 1999 9 34 (Pubitemid 129682569)
10. P. Bollmann-Sdorra, S.K.M. Wong, and Y.Y. Yao A measure-theoretic axiomatization of fuzzy sets Fuzzy Sets and Systems 60 3 1993 295 307
11. B. Liu Uncertainty Theory: An introduction to its axiomatic foundations, Studies in Fuzziness and Soft Computing 2004 Springer Berlin
12. M. Kochen Applications of fuzzy sets in psychology L. Zadeh, K. Fu, K. Tanaka, M. Shimura, Fuzzy Sets and their Applications to Cognitive and Decision Processes 1975 Academic Press, Inc. New York 395 408
13. M.E. McCloskey, and S. Glucksberg Natural categories: well defined or fuzzy sets? Memory & Cognition 6 4 1978 462 472 (Pubitemid 10194257)
14. E.H. Rosch On the internal structure of perceptual and semantic categories T.E. Moore, Cognitive Development and the Acquisition of Language 1973 Academic Press New York 111 144
15. G.C. Oden Fuzzyiness in semantic memory: choosing exemplars of subjective categories Memory & Cognition 5 2 1977 198 204 (Pubitemid 8068804)
16. M.P. Jenkins, G.A. Gross, A. Bisantz, R. Nagi, Towards context-aware hard/soft information fusion: incorporating situationally qualified human observations into a fusion process for intelligence analysis, in: Presented at the Cognitive Methods in Situation Awareness and Decision Support (CogSIMA2011), Miami Beach, FL, 2011.
17. J. Vestlund, L. Langeborg, P. Sörqvist, and M. Eriksson Experts on age estimation Scandinavian Journal of Psychology 50 2009 301 307
18. L.A. Zadeh Fuzzy sets as a basis for a theory of possibility theory Fuzzy Sets and Systems 1 1978 3 28
19. D. Dubois, and H. Prade On possibility/probability transformations Fuzzy Logic 1993 103 112
20. D. Dubois, and H. Prade Possibility Theory: An Approach to Computerized Processing of Uncertainty 1988 Plenum Press New York
21. G.J. Klir Principles of uncertainty: What are they? Why do we need them? Fuzzy Sets and Systems 74 1995 15 31
22. J.F. Geer, and G.J. Klir A mathematical analysis of information- preserving transformations between probabilistic and possibilistic formulations of uncertainty International Journal of General Systems 20 1992 143 176
23. G.J. Klir A principle of uncertainty and information invariance International Journal of General Systems 17 1990 249 275
24. D. Dubois, and H. Prade On several representations of an uncertain body of evidence Fuzzy Information and Decision Processes 1982 167 181 (Pubitemid 14645797)
25. D. Dubois, and H. Prade Fuzzy sets and statistical data European Journal of Operational Research 25 1986 345 356
26. V. Lasserre, G. Mauris, L. Foulloy, A simple probability-possibility transformation for measurement error representation: a truncated triangular transformation, in: Presented at the IFSA'97, Prague, 1997.
27. G. Mauris, V. Lasserre, and L. Foulloy Fuzzy modeling of measurement data acquired from physical sensors IEEE Transactions on Instrumentation and Measurement 49 2000
28. D. Dubois, and H. Prade Unfair coins and necessity measures: a possibilistic interpretation of histograms Fuzzy Sets and Systems 10 1983 15 20 (Pubitemid 14452042)
29. D. Conte, P. Foggia, C. Sansone, and M. Vento Thirty years of graph matching in pattern recognition International Journal of Pattern Recognition and Artificial Intelligence 18 2004 265 298
30. B. Huet, and E.R. Hancock Shape recognition from large image libraries by inexact graph matching Pattern Recognition Letters 20 1999 1259 1269 (Pubitemid 32261904)
31. G. Chin, Jr., O.A. Kuchar, P.D. Whitney, M.E. Powers, K.E. Johnson, Graph-based comparisons of scenarios in intelligence analysis, in: Presented at the 2004 IEEE International Conference on Systems, Man and Cybernetics, 2004.
32. T. Coffman, S. Greenblatt, and S. Marcus Graph-based technologies for intelligence analysis Communications of the AMC 47 2004 45 47
33. K.S. Booth Isomorphism testing for graphs, semigroups, and finite automata are polynomially equivalent problems SIAM Journal of Computation 7 3 1978 273 279
34. E.M. Luks Isomorphism of graphs of bounded valence can be tested in polynomial time Journal of Computer and System Sciences 25 1 1982
35. J.E. Hopcroft, J.K. Wong, Linear time algorithm for isomorphism of planar graphs, in: Proceedings of the Sixth Annual ACM Symposium on Theory of Computing, pp. 172-184.
36. S.A. Cook, The complexity of theorem-proving procedures, in: Proceedings 3rd Annual ACM Symposium on Theory of Computing, Association for Computing Machinery, New York, 1971, 151-158.
37. K. Sambhoos, R. Nagi, M. Sudit, and A. Stotz Enhancements to high level data fusion using graph matching and state space search Information Fusion 11 2010 351 364
38. K. Sambhoos, J. Llinas, E. Little, Graphical methods for real-time fusion and estimation with soft message data, in: Presented at the 11th International Conference on Information Fusion, Cologne, Germany, 2008.
39. W. Voxman Some remarks on distances between fuzzy numbers Fuzzy Sets and Systems 100 1998 353 365 (Pubitemid 128654415)
40. D. Guha, and D. Chakraborty A new approach to fuzzy distance measure and similarity measure between two generalized fuzzy numbers Applied Soft Computing 10 2010 90 99
41. M. Delgado, A. Vila, and W. Voxman On a canonical representation of fuzzy numbers Fuzzy Sets and Systems 93 1998 125 135 (Pubitemid 128654361)
42. M.Z. Angiz, S. Saati, A. Memariani, and M.M. Movahedi Solving possibilistic linear programming problem considering membership function of the coefficients Advances in Fuzzy Sets & Systems 1 2006 131 142
43. A. Kumar, A. Gupta, and A. Kaur Method for solving fully fuzzy assignment problems using triangular fuzzy numbers International Journal of Computer and Information Engineering 3 2009 231 234
44. C.-J. Lin, and U.-P. Wen Labeling algorithm for the fuzzy assignment problem Fuzzy Sets and Systems 142 2004 373 391
45. S.-M. Chen, and J.-H. Chen Fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads Expert Systems with Applications 36 2009 6833 6842
46. R.R. Yager, Ranking fuzzy subsets over the unit interval, in: 17th International Conference on Decision and Control, San Diego, California, 1978, pp. 1435-1437.
47. S. Murakami, S. Maeda, S. Imamura, Fuzzy decision analysis on the development of centralized regional energy control system, in: IFAC Symposium on Fuzzy Information, Knowledge Representation, and Decision Analysis, 1983, pp. 363-368.
48. C.H. Cheng A new approach for ranking fuzzy numbers by distance method Fuzzy Sets and Systems 95 1998 307 317
49. S.J. Chen, and S.M. Chen A new method for handling multicriteria fuzzy decision-making problems using FN-IOWA operators Cybernetics and Systems 34 2003 109 137
50. A.D. Stotz, Advancements in Computational Situation Assessment with Dynamic Graph-Based Procedures, Dissertation, University at Buffalo, 2009.
51. A. Stotz, R. Nagi, M. Sudit, Incremental graph matching for situation awareness, in: 12th International Conference on Information Fusion, Seattle, WA, 2009.
52. G.A. Gross, Graph Analytic Fusion Processing in Intelligence Analysis (in progress), Dissertation, University at Buffalo, 2011.
53. U. States, FM 34-8-2 Intelligence Officer's Handbook, D. o. t. Army, Ed., ed. Washington, DC, 1998.
54. J.L. Graham, D.L. Hall, J. Rimland, A synthetic dataset for evaluating soft and hard fusion algorithms, in: SPIE - Defense Transformation and Net-Centric Systems 2011, 2011.
55. M. Gjoka, M. Kurant, C.T. Butts, and A. Markopoulou Practical recommendations on crawling online social networks IEEE Journal on Selected Areas in Communications 29 9 2011 1872 1892
56. L. Page, S. Brin, R. Motwani, T. Winograd, The PageRank Citation Ranking: Bringing Order to the Web, Technical Report, Stanford University, Stanford, CA, 1998.
57. CPLEX 12.4 < http://www-01.ibm.com/software/integration/optimization/ cplex-optimizer/ >.