Abstract
In this paper, we apply possibilistic reasoning to information retrieval for documents endowed with similarity relations. On the one hand, it is used together with Boolean models for accommodating possibilistic uncertainty. The logical uncertainty principle is then interpreted in the possibilistic framework. On the other hand, possibilistic reasoning is integrated into description logic and applied to some information retrieval problems, such as query relaxation, query restriction, and exemplar-based retrieval.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
P. Blackburn. “Representation, reasoning, and relational structures: a hybrid logic manifesto”. Logic Journal of IGPL, 8(3):339–365, 2000.
M. Dalal. “Investigations into a theory of knowledge base revision: Preliminary report”. In Proceedings of the 7th National Conference on Artificial Intelligence, pages 475–479. AAAI Press, 1988.
D. Dubois, J. Lang, and H. Prade. “Possibilistic logic”. In D.M. Gabbay, C.J. Hogger, and J.A. Robinson, editors, Handbook of Logic in Artificial Intelligence and Logic Programming, Vol 3: Nonmonotonic Reasoning and Uncertain Reasoning, pages 439–513. Clarendon Press-Oxford, 1994.
F. Esteva, P. Garcia, L. Godo, and R. Rodriguez. “A modal account of similaritybased reasoning”. International Journal of Approximate Reasoning, pages 235–260, 1997.
A. Hunter. “Using default logic in information retrieval”. In C. Froidevaux and J. Kohlas, editors, Symbolic and Quantitative Approaches to Reasoning and Uncertainty: European Conference ECSQARU’95, LNAI 946, pages 235–242. Springer-Verlag, 1995.
M. Lalmas. “Dempster-Shafer’s theory of evidence applied to structured documents: modelling uncertainty”. In Proceedings of the 20th Annual International ACM SIGIR Conference in Research and Development of Information Retrieval, pages 110–118. ACM Press, 1997.
M. Lalmas. “Information retrieval and Dempster-Shafer’s theory of evidence”. In A. Hunter and S. Parsons, editors, Applications of Uncertainty Formalisms, LNAI 1455, pages 157–176. Springer-Verlag, 1998.
M. Lalmas. “Logical models in information retrieval: introduction and overview”. Information Processing and Management, 34(1):19–33, 1998.
M. Lalmas and P. Bruza. “The use of logic in information retrieval modeling”. Knowledge Engineering Review, 13(3):263–295, 1998.
C.J. Liau and I.P. Lin. “Possibilistic Reasoning—A Mini-survey and Uniform Semantics”. Artificial Intelligence, 88:163–193, 1996.
D.E. Losada and A. Barreiro. “Using a belief revision operator for document ranking in extended boolean models”. In Proceedings of the 22nd Annual International ACM SIGIR Conference in Research and Development of Information Retrieval, pages 66–73. ACM Press, 1999.
C. Meghini, F. Sebastiani, U. Straccia, and C. Thanos. “A model of information retrieval based on a terminological logic”. In Proceedings of the 16th Annual International ACM SIGIR Conference in Research and Development of Information Retrieval, pages 298–307. ACM Press, 1993.
C. Meghini and U. Straccia. “A relevance terminological logic for information retrieval”. In Proceedings of the 19th Annual International ACM SIGIR Conference in Research and Development of Information Retrieval, pages 197–205. ACM Press, 1996.
J.Y. Nie. “An information retrieval based on modal logic”. Information Processing and Management, 25(5):477–491, 1989.
J.Y. Nie. “Using fuzzy modal logic for inferential information retrieval”. Informatica, 20:299–318, 1996.
T. Rölleke and N. Fuhr. “Retrieval of complex objects using a four-valued logic”. In Proceedings of the 19th Annual International ACM SIGIR Conference in Research and Development of Information Retrieval, pages 206–214. ACM Press, 1996.
E. Ruspini. “On the semantics of fuzzy logic”. Int. J. of Approximate Reasoning, 5:45–88, 1991.
M. Schmidt-Schauβ and G. Smolka. “Attributive concept descriptions with complements”. Artificial Intelligence, 48(1):1–26, 1991.
F. Sebastiani. “A probabilistic terminological logic for modelling of information retrieval”. In W.B. Croft and C.J. van Rijsbergen, editors, Proceedings of the 17th Annual International ACM SIGIR Conference in Research and Development of Information Retrieval, pages 122–130. ACM Press, 1994.
C.J. van Rijsbergen. “A non-classical logic for information retrieval”. The Computer Journal, 29:481–485, 1986.
L.A. Zadeh. “Fuzzy sets as a basis for a theory of possibility”. Fuzzy Sets and Systems, 1(1):3–28, 1978.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liau, CJ., Yao, Y.Y. (2001). Information Retrieval by Possibilistic Reasoning. In: Mayr, H.C., Lazansky, J., Quirchmayr, G., Vogel, P. (eds) Database and Expert Systems Applications. DEXA 2001. Lecture Notes in Computer Science, vol 2113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44759-8_7
Download citation
DOI: https://doi.org/10.1007/3-540-44759-8_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42527-4
Online ISBN: 978-3-540-44759-7
eBook Packages: Springer Book Archive