“Why was This Item Retrieved?”: New Ways to Explore Retrieval Results

  • Ulrich Thiel
  • Adrian Müller
Part of the Information Retrieval and Hypertext book series (EPUB)


In an information seeking situation, humans can rely on a broad variety of behavioural patterns, and are generally very good at choosing appropriate ones and combining them. Most of these patterns, however, can be regarded as a specific realization of one of two general search principles, i.e. specify the properties of an item and interest, retrieve matching items and scan them for relevant ones vs. explore the neighbourhood and decide for each item found, whether it is of interest. We will refer to the first strategy as “matching”, while the second will be called “exploration” in the sequel.


Information Retrieval Classical Logic Intuitionistic Logic Information Item Information Retrieval System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    Croft, W.B. and Thompson, R.H. (1987). I 3 R: A New Approach to the Design of Document Retrieval Systems. Journal of the ASIS, 38(6), 389–404.Google Scholar
  2. [2]
    Doyle, L.B. (1975). Information Retrieval and Processing. Melville Publishing Co, Los Angeles, CA (USA).Google Scholar
  3. [3]
    Dummet, M. (1977). Elements of Intuitionism. Oxford University Press.Google Scholar
  4. [4]
    Fischer, G. and Nieper, (1989). Helgon: Extending the Retrieval by Reformulation Paradigm. Boulder, CO: Univ. of Colorado (Technical Report).Google Scholar
  5. [5]
    International Organization for Standardization. (1986). Information Processing — Text and Office Systems — Standardized Generalized Markup Language (SGML), 1986.Google Scholar
  6. [6]
    Nie, J-Y. (1992). Towards a Probabilistic Modal Logic for Semantic-Based Information Retrieval. In N.J. Belkin, P. Ingwersen and A.M Pejtersen (Eds.), Proc. SIGIR Conference, Copenhagen (Denmark), 140–151.Google Scholar
  7. [7]
    Rostek, L., Möhr, W.M. and Fischer, D. (1994). Weaving a Web: the Structure and Creation of an Object Network Representing an Electronic Reference Work. In C. Hüser, W. Möhr and V. Quint (Eds.), Proc. 5th. Int. Conference on Electronic Publishing, Document Manipulation and Typography, 495–505.Google Scholar
  8. [8]
    Thiel, U. and Hammwöhner, R. (1987). Informational Zooming: An Interaction Model for the Graphical Access to Text Knowledge Bases. In C.T. Yu and C.J. van Rijsbergen (Eds.), Proc. 10th. ACM-SIGIR Conference, New Orleans, (USA), 45–56.Google Scholar
  9. [9]
    Tou, F., Williams, M., Fikes, R., Henderson, D.A. and Malone, T. (1982). RABBIT: An Intelligent Database Assistant. In AAAI-82: Proc. Nat. Conference on Artificial Intelligence, 314–318.Google Scholar
  10. [10]
    van Rijsbergen, C.J. (1989). Towards an Information Logic. In N.J. Belkin and C.J. van Rijsbergen (Eds.), Proc. 12th ACM-SIGIR Conference, Boston, (USA), 77–86.Google Scholar

Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Ulrich Thiel
    • 1
  • Adrian Müller
    • 1
  1. 1.GMD-IPSIGermany

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