A probabilistic quantifier fuzzification mechanism: The model and its evaluation for information retrieval

IEEE Transactions on Fuzzy Systems

Volumn 13, Issue 5, 2005, Pages 688-700

  Díaz Hermida, Felix ^a   Losada, David E ^a   Bugarín, Alberto ^a   Barro, Senén ^a  

^a UNIVERSITY OF SANTIAGO DE COMPOSTELA   (Spain)

Author keywords

Fuzzy quantification; Information retrieval; Quantifier fuzzification mechanisms

Indexed keywords

ALGORITHMS; EVALUATION; INFORMATION RETRIEVAL; MATHEMATICAL MODELS; PERFORMANCE; PROBABILITY;

FUZZY QUANTIFICATION; QUANTIFIER FUZZIFICATION MECHANISMS;

FUZZY SETS;

EID: 27644578727     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2005.856557     Document Type: Article

References (31)

1. P. Bosc, L. Lietard, and O. Pivert, "Quantified statements and database fuzzy querying," in Fuzziness in Database Management Systems. ser. Studies in Fuzziness, P. Bosc and J. Kacprzyk, Eds. Heidelberg, Germany: Physica-Verlag, 1995, vol. 5, pp. 275-308.
2. R. R. Yager, "Approximate reasoning as a basis for rule-based expert systems," IEEE Trans. Syst., Man, Cybern., vol. SMC-14, no. 4, pp. 636-642, Jul. 1984.
3. M. Delgado, D. Sánchez, and M. A. Vila, Fuzzy Logic in Medicine, ser. Studies in Fuzziness and Soft Computing. Heidelberg, Germany: Physica-Verlag, 2002, vol. 83, ch. Acquisition of Fuzzy Association Rules from Medical Data, pp. 286-310.
4. L. Zadeh, "A computational approach to fuzzy quantifiers in natural languages," Comp. Mach. Appl., vol. 8, pp. 149-184, 1983.
5. I. Glöckner and A. Knoll, "A formal theory of fuzzy natural language quantification and its role in granular computing," in Granular Computing: An Emerging Paradigm. ser. Studies in Fuzziness and Soft Computing, W. Pedrycz, Ed. Heidelberg, Germany: Physica-Verlag, 2001, vol. 70, pp. 215-256.
6. I. Glöckner, "DPS - An Axiomatic Approach to Fuzzy Quantification," Univ. Bielefeld, Bielefeld, Germany, Techn. Fakultat tR97-06, 1997.
7. I. Glöckner, "Fuzzy quantifiers in natural language: Semantics and computational models," Ph.D. fissertation, Univ. Bielefeld, Bielefeld, Germany, 2003.
8. G. Bordogna and G. Pasi, "Linguistic aggregation operators of selection criteria in fuzzy information retrieval," Int. J. Intell. Syst., vol. 10, no. 2, pp. 233-248, 1995.
9. D. E. Losada, F. Díaz-Hermida, A. Bugarín, and S. Barro, "Experiments on using fuzzy quantified sentences in adhoc retrieval," in Proc. SA C-04, 19th ACM Symp. Applied Computing-Special Track on Information Access and Retrieval, Nicosia, Cyprus, Mar. 2004, pp. 1059-1066.
10. J. Baldwin, J. Lawry, and T. Martin, "Mass assignment theory of the probability of fuzzy events," Fuzzy Sets Syst., vol. 83, pp. 353-367, 1996.
11. S. Thomas, Fuzziness and Pobability. Wichita, KS: ACG Press, 1995.
12. F. Díaz-Hermida, A. Bugarín, P. Cariñena, and S. Barro, "Voting model based evaluation of fuzzy quantified sentences: A general framework," Fuzzy Sets Syst., vol. 146, pp. 97-120, 2004.
13. S. Barro, A. Bugarín, P. Cariñena, and F. Díaz-Hermida, "A framework for fuzzy quantification models analysis," IEEE Trans. Fuzzy Syst., vol. 11, no. 1, pp. 89-99, Feb. 2003.
14. R. Kruse, J. Gebhardt, and F. Klawonn, Foundations of Fuzzy Systems. New York: Wiley, 1994.
15. M. Delgado, D. Sánchez, and M. A. Vila, "Fuzzy cardinality based evaluation of quantified sentences," Int. J. Approx. Reason., vol. 23, no. 1, pp. 23-66, 2000.
16. R. Yager, "On ordered weighted averaging aggregation operators in multicriteria decisionmaking," IEEE Trans. Syst., Man, Cybern., vol. 18, no. 1, pp. 183-191, Jan. 1988.
17. F. Díaz-Hermida, A. Bugarín, and S. Barro, "Definition and classification of semifuzzy quantifiers for the evaluation of fuzzy quantified sentences," Int. J. Approx. Reason., vol. 34, no. 1, pp. 49-88, 2003.
18. I. Glöckner, "Evaluation of quantified propositions in generalized models of fuzzy quantification," Int. J. Appmx. Reason., vol. 37, pp. 93-126, 2004.
19. F. Díaz-Hermida, D. Losada, A. Bugarín, and S. Barro, "Analysis of a probabilistic quantifier fuzzification mechanism," Univ. Santiago de Compostela, Santiago de Compostela, Spain, Tech. Rep. GSI-04-01, 2004.
20. C. van Rijsbergen, "A nonclassical logic for information retrieval," Comput. J., vol. 29, pp. 481-485, 1986.
21. F. Crestani, M. Lalmas, and C. J. van Rijsbergen, Eds., Information Retrieval, Uncertainty and Logics: Advanced Models for the Representation and Retrieval ofinformation. Norwell, MA: Kluwer, 1998.
22. S. E. Robertson and K. S. Jones, "Relevance weighting of search terms," J. Amer. Soc. Inform. Sci., vol. 27, no. 3, pp. 129-146, 1976.
23. K. S. Jones, S. Walker, and S. E. Robertson, "A probabilistic model of information retrieval: Development and comparative experiments," Inform. Process. Manage., vol. 36, pp. 779-840, 2000.
24. G. Salton and M. McGill, Introduction to Modern Information Retrieval. New York: McGraw-Hill, 1983.
25. A. Singhal, C. Buckley, and M. Mitra, "Pivoted document length normalization," in Proc. SIGIR-96, 19th ACM Conf.Research and Development in Information Retrieval, Zurich, Switzerland, Jul. 1996, pp. 21-29.
26. S. Robertson and S. Walker, "Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval," in Proc. SIGIR-94, 17th ACM Conf. Research and Development in Information Retrieval, Dublin, Ireland, Jul. 1994, pp. 232-241.
27. J. Ponte and W. B. Croft, "A language modeling approach to information retrieval," in Proc. 21st ACM Conf.Research and Development in Information Retrieval, SIGIR'98, Melbourne, Australia, 1998, pp. 275-281..
28. TREC: The Text Retrieval Conference [Online]. Available: http://trec. nist.gov.
29. M. Porter, "An algorithm for suffix stripping," in Readings in Information Retrieval, K. Jones and P. Willet, Eds. San Mateo, CA: Morgan Kaufmann, 1997, pp. 313-316.
30. GNU Mifluz [Online]. Available: http://www.gnu.org/software/mifluz
31. D. Harman, "Overview of the third text retrieval conference," in Proc. TREC-3, 3rd Text Retrieval Conf., 1994.