Mathematical, logical, and formal methods in information retrieval: an introduction to the special issue

ABSTRACT

Research on the use of mathematical, logical, and formal methods, has been central to Information Retrieval research for a long time. Research in this area is important not only because it helps enhancing retrieval effectiveness, but also because it helps clarifying the underlying concepts of Information Retrieval. In this article we outline some of the major aspects of the subject, and summarize the papers of this special issue with respect to how they relate to these aspects. We conclude by highlighting some directions of future research, which are needed to better understand the formal characteristics of Information Retrieval.

REFERENCES

• 1: Peter Bollmann-Sdorra , Vijay V. Raghavan, On the delusiveness of adopting a common space for modeling IR objects: are queries documents?, Journal of the American Society for Information Science, v.44 n.10, p.579-587, Dec. 1993 [doi>10.1002/(SICI)1097-4571(199312)44:10<579::AID-ASI3>3.0.CO;2-B]
• 2: Peter Bollmann-Sdorra , Vijay V. Raghavan, On the necessity of term dependence in a query space for weighted retrieval, Journal of the American Society for Information Science, v.49 n.13, p.1161-1168, Nov. 1998 [doi>10.1002/(SICI)1097-4571(1998)49:13<1161::AID-ASI3>3.0.CO;2-2]
• 3: E. F. Codd, A relational model of data for large shared data banks, Communications of the ACM, v.13 n.6, p.377-387, June 1970 [doi>10.1145/362384.362685]
• 4: Crestani, F., & van Rijsbergen, C.J. (1995).Information retrieval by logical imaging. Journal of Documentation, 51(1), 3-17.
• 5: Mounia Lalmas , Cornelis Joost Van Rijsbergen, Information Retrieval: Uncertainty and Logics: Advanced Models for the Representation and Retrieval of Information, Kluwer Academic Publishers, Norwell, MA, 1998
• 6: Crestani, F., & Pasi, G. (Eds.). (2000). Soft computing in information retrieval: Techniques and applications. Heidelberg, German: Physica-Verlag (Springer-Verlag).
• 7: Keith Devlin, Logic and information, Cambridge University Press, New York, NY, 1991
• 8: Dominich, S. (2001). Mathematical foundations of information retrieval. Dordrecht, The Netherlands: Kluwer Academic Publishers.
• 9: Leo Egghe , Ronald Rousseau, Topological aspects of information retrieval, Journal of the American Society for Information Science, v.49 n.13, p.1144-1160, Nov. 1998 [doi>10.1002/(SICI)1097-4571(1998)49:13<1144::AID-ASI2>3.0.CO;2-Z]
• 10: Norbert Fuhr , Thomas Rölleke, HySpirit - A Probabilistic Inference Engine for Hypermedia Retrieval in Large Databases, Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology, p.24-38, March 23-27, 1998
• 11: Daqing He , Ayse Göker , David J. Harper, Combining evidence for automatic web session identification, Information Processing and Management: an International Journal, v.38 n.5, p.727-742, September 2002 [doi>10.1016/S0306-4573(01)00060-7]
• 12: Mounia Lalmas, Logical models in information retrieval: introduction and overview, Information Processing and Management: an International Journal, v.34 n.1, p.19-33, 1998 [doi>10.1016/S0306-4573(97)00041-1]
• 13: Lalmas, M., & van Rijsbergen, C.J. (1992). A logical model of information retrieval based on situation theory. Proceedings of the BCS 14th information retrieval colloquium, Lancaster (pp. 1-13).
• 14: M. E. Maron , J. L. Kuhns, On Relevance, Probabilistic Indexing and Information Retrieval, Journal of the ACM (JACM), v.7 n.3, p.216-244, July 1960 [doi>10.1145/321033.321035]
• 15: Stefano Mizzaro, Relevance: the whole history, Journal of the American Society for Information Science, v.48 n.9, p.810-832, Sept. 1997 [doi>10.1002/(SICI)1097-4571(199709)48:9<810::AID-ASI6>3.0.CO;2-U]
• 16: S. E. Robertson , S. Walker, Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval, Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, p.232-241, July 03-06, 1994, Dublin, Ireland
• 17: G. Salton , A. Wong , C. S. Yang, A vector space model for automatic indexing, Communications of the ACM, v.18 n.11, p.613-620, Nov. 1975 [doi>10.1145/361219.361220]
• 18: Shannon, C. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, 379-423, 623-656.
• 19: C. J. Van Rijsbergen, Information Retrieval, Butterworth-Heinemann, Newton, MA, 1979
• 20: C J Van Rijsbergen, A new theoretical framework for information retrieval, ACM SIGIR Forum, v.21 n.1-2, p.23-29, Sept.-March 1986-1987 [doi>10.1145/24634.24635]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.1 Logical Design
          Subjects: Data models

General Terms:
Algorithms, Design