Logical and uncertainty models for information access: current trends

The current trends of research in information access as emerged from the 1999 Workshop on Logical and Uncertainty Models for Information Systems (LUMIS'99) are briefly reviewed in this paper. We believe that some of these issues will be central to future research on theory and applications of logical and uncertainty models for information access.

[1]  Sandor Dominich.  A Geometric View of Relevance Effectiveness in Information Retrieval , 2000 .

[2]  Mounia Lalmas,et al.  Information Retrieval: Uncertainty and Logics: Advanced Models for the Representation and Retrieval of Information , 1998 .

[3]  Van Rijsbergen,et al.  A theoretical basis for the use of co-occurence data in information retrieval , 1977 .

[4]  Fabio Crestani,et al.  “Is this document relevant?…probably”: a survey of probabilistic models in information retrieval , 1998, CSUR.

[5]  Theo Huibers,et al.  An axiomatic theory for information retrieval , 1996 .

[6]  Mounia Lalmas,et al.  Logical Models in Information Retrieval: Introduction and Overview , 1998, Inf. Process. Manag..

[7]  C. J. van Rijsbergen,et al.  A Non-Classical Logic for Information Retrieval , 1997, Comput. J..

[8]  P G rdenfors,et al.  Knowledge in flux: modeling the dynamics of epistemic states , 1988 .

[9]  Sergei Ovchinnikov,et al.  Fuzzy sets and applications , 1987 .

[10]  Fabio Crestani,et al.  Soft computing in information retrieval: techniques and applications , 2000 .

[11]  H. Prade,et al.  Some uses of fuzzy logic in multimedia databases querying , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[12]  Nikola Kasabov,et al.  Neuro-Fuzzy Techniques for Intelligent Information Systems , 1999 .

[13]  Jian-Yun Nie.  An outline of a general model for information retrieval systems , 1988, SIGIR '88.

[14]  William S. Cooper,et al.  Some inconsistencies and misidentified modeling assumptions in probabilistic information retrieval , 1995, TOIS.

[15]  W. Bruce Croft,et al.  I3R: A new approach to the design of document retrieval systems , 1987, J. Am. Soc. Inf. Sci..

[16]  W. Bruce Croft,et al.  I 3 R: a new approach to the design of document retrieval systems , 1987 .

[17]  Alistair Moffat,et al.  Exploring the similarity space , 1998, SIGF.

[18]  K. Shadan,et al.  Available online: , 2012 .

[19]  Peter Bruza,et al.  Query Reformulation on the Internet: Empirical Data and the Hyperindex Search Engine , 1997, RIAO.

[20]  Justin Picard.  Logic as a Tool in a Term Matching Information Retrieval System , 1999 .

[21]  Jacques Savoy,et al.  A Learning Scheme for Information Retrieval in Hypertext , 1994, Inf. Process. Manag..

[22]  D. Nute.  Topics in Conditional Logic , 1980 .

[23]  L. Zadeh,et al.  Fuzzy sets and applications : selected papers , 1987 .

[24]  Gianni Amati,et al.  A Logical approach to Query Reformulation motivated from Belief Change , 1999 .

[25]  Sally McClean,et al.  Text Passage Classification Using Supervised Learning , 1999 .

[26]  William S. Cooper,et al.  Some inconsistencies and misnomers in probabilistic information retrieval , 1991, SIGIR '91.

[27]  Fabio Crestani,et al.  Information Retrieval: Uncertainty and Logics , 1998, The Kluwer International Series on Information Retrieval.

[28]  Edie M. Rasmussen,et al.  Clustering Algorithms , 1992, Information Retrieval: Data Structures & Algorithms.

[29]  Fabio Crestani,et al.  A study of probability kinematics in information retrieval , 1998, TOIS.