Representation and reasoning under uncertainty in deception detection: A neuro-fuzzy approach

IEEE Transactions on Fuzzy Systems

Volumn 16, Issue 2, 2008, Pages 442-454

  Zhou, Lina ^a   Zenebe, Azene ^b  

^a Baltimore County   (United States)

^b BOWIE STATE UNIVERSITY   (United States)

Author keywords

Deception detection; Fuzzy sets; Fuzzy systems; Uncertainty

Indexed keywords

COGNITIVE SYSTEMS; FUZZY LOGIC; FUZZY SETS; LEARNING SYSTEMS; UNCERTAIN SYSTEMS;

COMPUTER-MEDIATED COMMUNICATION; DECEPTION DETECTION; HUMAN COGNITIVE MODEL;

FUZZY NEURAL NETWORKS;

EID: 42549153858     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2006.889914     Document Type: Article

References (60)

1. D. B. Buller and J. K. Burgoon, "Interpersonal deception theory," Commun. Theory, vol. 6, pp. 203-242, 1996.
2. L. Zhou, D. Twitchell, J. Burgoon, T. Qin, and J. Nunamaker, "A comparison of classification methods for predicting deception in computer-mediated communication," J. Manage. Inform. Syst., vol. 20, pp. 139-165, 2004.
3. J. K. Burgoon, J. P. Blair, T. Qin, and J. F. Nunamaker, "Detecting deception through linguistic analysis," presented at the 1st NSF/NIJ Symp. Intell. Security Informatics, Tucson, AZ, 2003, LNCS 2665, unpublished.
4. B. M. DePaulo, J. J. Lindsay, B. E. Malone, L. Muhlenbruck, K. Charlton, and H. Cooper, "Cues to deception," Psychol. Bull., vol. 129, pp. 74-112, 2003.
5. L. Zhou, "An empirical investigation of deception behavior in instant messaging," IEEE Trans. Prof. Commun., vol. 48, pp. 147-160, 2005.
6. L. Zhou, J. K. Burgoon, J. F. Nunamaker, and D. Twitchell, "Automated linguistics based cues for detecting deception in text-based asynchronous computer-mediated communication: An empirical investigation," Group Decision Negot., vol. 13, pp. 81-106, 2004.
7. D. P. Twitchell and D. P. Biros, "Automated determination of the veracity of interview statements from people of interest to an operational security force," presented at the 39th Hawaii Int. Conf. Syst. Sci., Kauai, HI, 2006, unpublished.
8. A. Vrij and S. Mann, "Detecting deception: The benefit of looking at a combination of behavioral, auditory, and speech content related cues in a systematic manner," Group Decision Negot., vol. 13, pp. 61-79, 2004.
9. J. K. Burgoon, N. Miczo, and L. A. Miczo, "Adaptation during deceptive interactions: Testing the effects of time and partner communication style," presented at the Nat. Commun. Assoc. Conv., Atlanta, GA, 2001, unpublished.
10. C. H. White and J. K. Burgoon, "Adaptation and communicative design: Patterns of interaction in truthful and deceptive conversation," Human Commun. Res., vol. 27, pp. 9-37, 2001.
11. L. Zhou, J. K. Burgoon, D. Zhang, and J. F. Nunamaker, "Language dominance in interpersonal deception via computer-mediated communication," Comput. Human Behav., vol. 20, pp. 381-402, 2004.
12. C. Joslyn and L. Rocha, "Towards a formal taxonomy of hybrid uncertainty representations," Inform. Sci., vol. 110, pp. 255-277, 1998.
13. L. A. Zadeh, "Fuzzy sets," Inform. Contr., vol. 8, pp. 338-353, 1965.
14. J.-Y. Mao and I. Benbasat, "The use of explanations in knowledge-based systems: Cognitive perspectives and a process-tracing analysis," J. Manage. Inform. Syst., vol. 17, pp. 153-179, 2000.
15. Z. Chen, Data Mining and Uncertain Reasoning: An Integrated Approach New York: Wiley, 2001.
16. R. Weber, "Customer segmentation for banks and insurance groups with fuzzy clustering techniques," in Fuzzy Logic, J. Baldwin, Ed. New York: Wiley, 1996, pp. 187-196.
17. G. Johnson and E. Santos, "Detecting deception in intelligent systems I: Activation of deception detection tactics," presented at the Adv. Artif. Intell. 17th Conf. Can. Soc. Comp. Studies Intell., Ontario, ON, Canada, 2004, LNCS, unpublished.
18. B. Yu and M. P. Singh, "Detecting deception in reputation management," presented at the 2nd Int. Joint Conf. Auton. Agents Multi-Agent Syst., Melbourne, Australia, 2003, unpublished.
19. J. K. Burgoon, J. P. Blair, and R. E. Strom, "Heuristics and modalities in determining truth versus deception," presented at the 38th Hawaii Int. Conf. Syst. Sci., Big Island, HI, 2005, unpublished.
20. B. M. DePaulo, J. T. Stone, and G. D. Lassiter, "Deceiving and detecting deceit," in The Self and Social Life, B. R. Schlenker, Ed. New York: McGraw-Hill, 1985, pp. 323-370, unpublished.
21. T. O. Boucher, "Reliability, validity, and imprecision in fuzzy multicriteria decision-making," IEEE Trans. Syst., Man, Cybern. C vol. 32, pp. 190-202, 2002.
22. N. S. Iyer, "A family of dominance rules for multiattribute decision making under uncertainty," IEEE Trans. Syst., Man, Cybern. A, vol. 33, pp. 441-450, 2003.
23. H. C. Bahl and R. G. Hunt, "Decision-making theory and DSS design," SIGMIS Database, vol. 15, pp. 10-14, 1984.
24. L. Zhou and A. Zenebe, "Modeling and handling uncertainty in deception detection," presented at the 38th Hawaii Int. Conf. Syst. Sci., Big Island, HI, 2005, unpublished.
25. G. J. Klir and T. A. Folger, "," in Fuzzy Sets, Uncertainty, and Information. Englewood Cliffs, NJ: Prentice-Hall, 1988, unpublished.
26. P. Smets, "Theories of uncertainty," in Handbook of Fuzzy Computation, E. Ruspini, P. P. Bonissone, and W. Pedrycz, Eds. Philadelphia, PA: Institute of Physics, 1999, unpublished.
27. M. Smithson, Ignorance and Uncertainty: Emerging Paradigms. New York: Springer-Verlag, 1989.
28. R. L. Daft and R. H. Lengel, "Organizational information requirements, media richness and structural design," Manage. Sci., vol. 32, pp. 554-571, 1986.
29. C. Olaru and L.Wehenkel, "A complete fuzzy decision tree technique," Fuzzy Sets Syst., vol. 138, pp. 221-254, 2003.
30. T. G. Dietterich and E. B. Kong, Machine learning bias, statistical bias, and statistical variance of decision tree algorithms Dept. of Comput. Sci., Oregon State Univ., Tech. Rep., 1995.
31. L. L. Kuncheva, Fuzzy Classifier Design. New York: Springer-Verlag, 2000, vol. 49.
32. J. H. Friedman, Local learning based on recursive covering Dept. of Statistics, Stanford Univ., Technical Rep., Aug. 1996.
33. S. P. Curram and J. Mingers, "Neural networks, decision tree induction and discriminant analysis: An empirical comparison," J. Oper. Res. Soc., vol. 45, pp. 440-450, 1994.
34. D. Nauck, F. Klawonn, and R. Kruse, Foundations of Neuro-Fuzzy Systems. Chichester, U.K.: Wiley, 1997.
35. Q. Chen, "Pattern recognition and classification in user modeling: A neural network approach," in Information Systems. Baltimore, MD: Univ. of Maryland Baltimore County, 1995, p. 174.
36. J. Pearl, "Decision making under uncertainty," ACM Comput. Surv. vol. 28, pp. 89-92, 1996.
37. L. A. Zadeh, "Fuzzy logic, neural networks, and soft computing," Commun. ACM, vol. 37, pp. 77-84, 1994.
38. S. Abe, Pattern Classification: Neuro-Fuzzy Methods and Their Comparison. London, U.K.: Springer-Verlag, 2001.
39. M. Goebel and L. Gruenwald, "A survey of data mining and knowledge discovery software tools," SIGKDD Explor. Newsl., vol. 1, pp. 20-33, 1999.
40. E. Cox, The Fuzzy Systems Handbook, 2nd ed. New York: AP Professional, 1999.
41. T. Bilgiç and I. B. Turksen, "Measurement of membership functions: Theoretical and empirical work," in Fundamentals of Fuzzy Sets, Vol. 1, Handbook of Fuzzy Sets and Systems, D. Dubois and H. Prade, Eds. Boston, MA: Kluwer, 1999, pp. 195-232.
42. D. Nauck and R. Kruse, "Obtaining interpretable fuzzy classification rules from medical data," Artif. Intell. Med., vol. 16, pp. 149-169, 1999.
43. D. Chakraborty and N. R. Pal, "A neuro-fuzzy scheme for simultaneous feature selection and fuzzy rule-based classification," IEEE Trans. Neural Netw., vol. 15, pp. 110-123, 2004.
44. B. M. DePaulo, M. Zuckerman, and R. Rosenthal, "Detecting deception: Modality effects," in Review of Personality and Social Psychology L. Wheeler, Ed. Beverly Hills, CA: Sage, 1980, pp. 125-162.
45. G. A. Giordano and J. F. George, "Task complexity and deception detection in a collaborative group setting," presented at the 38th Hawaii Int. Conf. Syst. Sci., Big Island, HI, 2005, unpublished.
46. D. E. Rumerlhart and J. L. McClelland, Parallel and Distributed Processing: Exploration in the Microstructure of Cognition. Cambridge, MA: MIT Press, 1986.
47. J. R. Quinlan, C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufmann, 1993.
48. T. G. Dietterich, "Approximate statistical tests for comparing supervised classification learning algorithms," Neural Comput., vol. 10, pp. 1895-1923, 1998.
49. R. Bouckaert and E. Frank, "Evaluating the replicability of significance tests for comparing learning algorithms," presented at the Pacific-Asia Conf. Knowl. Discovery Data Mining, Sydney, Australia, 2004, unpublished.
50. C. Nadeau and Y. Bengio, "Inference for the generalization error," Machine Learn., vol. 52, pp. 239-281, 2003.
51. A. R. Dennis and S. T. Kinney, "Testing media richness theory in the new media: The effects of cues, feedback, and task equivocality," Inform. Syst. Res., vol. 9, pp. 256-274, 1998.
52. J. E. McGrath, Groups: Interaction and Performance. Englewood Cliffs, NJ: Prentice-Hall, 1984.
53. T. Qin, J. Burgoon, J. P. Blair, and J. Nunamaker, "Modality effects in deception detection and applications in automatic deception detection," presented at the 38th Hawaii Int. Conf. Syst. Sci., Big Island, HI, 2005, unpublished.
54. J. K. Burgoon, L. Dillman, and L. A. Stern, "Adaptation in dyadic interaction: Defining and operationalizing patterns of reciprocity and compensation," Commun. Theory, vol. 3, pp. 295-316, 1993.
55. M. E. Roloff, "Communication and reciprocity within intimate relationships," in Interpersonal Processes: New Directions in Communication Research, M. E. Roloff and G. R. Miller, Eds. Beverly Hills, CA: Sage, 1987, pp. 11-38.
56. R. R. Yager, "Fuzzy modeling for intelligent decision making under uncertainty," IEEE Trans. Syst., Man, Cybern., vol. 30, pp. 60-70, 2000.
57. D. W. Straub and R. J. Welke, "Coping with systems risk: Security models for management decision-making," MIS Quart., vol. 22, pp. 441-469, 1998.
58. A. Vyas and L. Zhou, "On detecting deception in agent societies," presented at the IEEE/WIC/ACM Int. Joint Conf. Web Intelligence Intelligent Agent Technol.,, France, 2005, Compiegne Univ. of Technol., unpublished.
59. Y.-S. Chen and C. Shahabi, "Automatically improving the accuracy of user profiles with genetic algorithm," in Proc. IASTED Int. Conf. Artif. Intell. Soft Comput., Cancun, Mexico, 2001.
60. O. Cordon, F. Herrera, F. Hoffmann, and L. Magdalena, Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, ser. Advances in Fuzzy Systems - Applications and Theory. Singapore: World Scientific, 2001, vol. 19.