Understanding and Supporting Human Information Seeking

  • Nicholas J. Belkin
Part of the Astrophysics and Space Science Library book series (ASSL, volume 182)


What would constitute “intelligent” information retrieval is a question which has had a variety of answers over the twenty or so years that the concept has been extant. This paper reviews some of the approaches to intelligent information retrieval that have been suggested. Most of these suggestions have shared the assumption that the “intelligence” resides solely in the built system. More recent work in information retrieval has begun to concentrate on the interaction between the user and the other components of the system, and this work leads to an alternative assumption: that the user is an integral part of the information retrieval system, and that intelligence in the system resides in appropriate distribution of tasks between the user and the built system. We review some of this newer work, and propose an approach to the design of information retrieval systems starting from this new assumption. The approach is based upon three principles: that information retrieval is a process in support of the user’s more general domain and task environment; that people engage in a variety of information seeking strategies, all of which should be supported by the information retrieval system; and, that information retrieval is an inherently interactive process among user, knowledge resources, and intermediary mechanisms. These principles lead to prescriptions for domain, work and task analysis, for study of information seeking strategies and their relationships to underlying tasks, and for system design to support cooperative interaction among the participants.


Information Retrieval Belief Revision Information Retrieval System Knowledge Resource Task Environment 
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.
    Belew, R.K., “Adaptive information retrieval”, Proceedings of the 12th International Conference on Research and Development in Information Retrieval, ACM, New York, 11–20, 1989.Google Scholar
  2. 2.
    Belkin, N.J., Cool, C., Stein, A. and Thiel, U., Preprints of the AAAI Spring Symposium on Case-Based Reasoning and Information Retrieval, March 1993b.Google Scholar
  3. 3.
    Belkin, N.J. and Croft, W.B., “Information filtering and information retrieval: two sides of the same coin?”, Communications of the ACM, 35, 29–38, 1992.CrossRefGoogle Scholar
  4. 4.
    Belkin, N.J., Marchetti, EG. and Cool, C, “BRAQUE: Design of an interface to support user interaction in information retrieval”, Information Processing and Management, 29, 1993a (in press).Google Scholar
  5. 5.
    Belkin, N.J., Seeger, T. and Wersig, G., “Distributed expert problem treatment as a model for information system analysis and design”, Journal of Information Science, 5, 153–167, 1983.CrossRefGoogle Scholar
  6. 6.
    Belkin, N.J. and Vickery, A., Interaction in Information Systems, The British Library, London, 1985.Google Scholar
  7. 7.
    Brajnik, G., Guida, G. and Tasso, C, “User modeling in intelligent information retrieval”, Information Processing and Management, 23, 305–320, 1987.CrossRefGoogle Scholar
  8. 8.
    Cawsey, A., Galliers, J., Reece, S. and Sparck Jones, K., “Automating the librarian: belief revision as a base for system action and communication with the user”, The Computer Journal, 35, 221–232, 1992.CrossRefGoogle Scholar
  9. 9.
    Croft, W.B., “Approaches to intelligent information retrieval”, Information Processing and Management, 23, 249–254, 1987.CrossRefGoogle Scholar
  10. 10.
    Croft, W.B. and Thompson, R.H., “I3R: a new approach to the design of document retrieval systems”, Journal of the American Society for Information Science, 38, 389–404. 1987.CrossRefGoogle Scholar
  11. 11.
    Daniels, P.J., “Cognitive modeling in information retrieval — an evaluative review”, Journal of Documentation, 42, 272–304, 1986.Google Scholar
  12. 12.
    Egan, D.E. et al., “Formative design-evaluation of Super-Book”, ACM Transactions on Information Systems, 7, 30–57, 1989.CrossRefGoogle Scholar
  13. 13.
    Foltz, P.W. and Dumais, S.T., “Personalized information delivery: an analysis of information filtering methods”, Communications of the ACM, 35, 51–60, 1992.CrossRefGoogle Scholar
  14. 14.
    Furnas, G.W., Landauer, T.K., Gomez, L.M. and Dumais, ST., “Statistical semantics: analysis of the potential performance of keyword information systems”, Bell Systems Technical Journal, 62, 1753–1806, 1983.Google Scholar
  15. 15.
    Giommi, P. et al., “The European Space Information System”, in A. Heck and F. Murtagh, eds., Astronomy from Large Databases II, European Southern Observatory, Garching, 289, 1992.Google Scholar
  16. 16.
    Harman, D., ed., The First Text Retrieval Conference, National Institute of Standards and Technology Special Publication 500–207, Gaithersburg, MD, 1993.Google Scholar
  17. 17.
    Ingwersen, P., Information Retrieval Interaction, Taylor Graham, London, 1992.Google Scholar
  18. 18.
    Liddy, E.D. and Myaeng, S.H., “DR-LINK: Document retrieval using linguistic knowledge. Project description.”, SIGIR Forum, 26, 39–43, 1992.CrossRefGoogle Scholar
  19. 19.
    Oddy, R.N., “Information retrieval through man-machine dialogue”, Journal of Documentation, 33, 1–14, 1977.Google Scholar
  20. 20.
    Salton, G. and Buckley, C, “Improving retrieval performance by relevance feedback”, Journal of the American Society for Information Science, 41, 288–297, 1990.CrossRefGoogle Scholar
  21. 21.
    Salton, G., Fox, E. and Wu, H., “Extended Boolean information retrieval”, Communications of the ACM, 26, 1022–1036, 1983.MATHCrossRefGoogle Scholar
  22. 22.
    Saracevic, T. and Kantor, P., “A study of information seeking and retrieving. III. Searchers, searches and overlap”, Journal of the American Society for Information Science, 39, 197–216, 1988.CrossRefGoogle Scholar
  23. 23.
    Su, L., “Evaluation measures for interactive information retrieval”, Information Processing and Management, 28, 503–516, 1992.CrossRefGoogle Scholar
  24. 24.
    Turtle, H. and Croft, W.B., “Evaluation of an inference network-based retrieval model”, ACM Transactions on Information Systems, 9, 187–222, 1991.CrossRefGoogle Scholar
  25. 25.
    van Rijsbergen, C.J., “A new theoretical framework for information retrieval”, Proceedings of the 1986 ACM SIGIR Conference, ACM, New York, 194–200, 1986.Google Scholar
  26. 26.
    Woods, D.D. and Roth, E.M., Handbook of Human-Computer Interaction, Elsevier/North-Holland, Amsterdam, 3–43, 1988.Google Scholar

Copyright information

© Kluwer Academic Publishers 1993

Authors and Affiliations

  • Nicholas J. Belkin
    • 1
  1. 1.School of Communication, Information and Library StudiesRutgers UniversityNew BrunswickUSA

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