BT Technology Journal

, Volume 25, Issue 3–4, pp 285–298 | Cite as

Networked information management

  • N. J. Davies
  • M. C. Revett
Breadth as well as depth


Every day millions of people trawl the Internet for information using any one of a dozen or more different search tools. Whether they find what they are looking for may depend not only on their skill, but also on their luck. In the corporate arena, organisations are making increasing amounts of information available via intranets. This paper looks at the limitations of current networked information management technology, in particular, shortcomings in the areas of retrieving, organising and sharing of information, and an information management process which would overcome these problems is described. The representation of a user’s information needs and interests in a user profile is seen to be central to the process and work in this area, including a novel, non-explicit approach to the representation of profiles, is covered. Four information access systems developed at BT Laboratories are discussed and the extent to which these are currently able to support the information management process is considered.


Information Retrieval User Profile Inverse Document Frequency Information Agent Remembrance Agent 
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.
    Pollock A and Hockley A: ’What’s Wrong with Internet Searching?’, Designing the Web, Empirical Studies conference, Microsoft Usability Group, Microsoft, Redmond, US (October 1996).Google Scholar
  2. 2.
    Cochrane R: ’Unleashing the intranet’, BT Technol J, 15, No 2, pp 107–113 (April 1997).CrossRefMathSciNetGoogle Scholar
  3. 3.
    Blair D C and Maron M E: ’An evaluation of retrieval effectiveness for a full-text document retrieval system’, Communications of the ACM, 28, No 3 (March 1985).Google Scholar
  4. 4.
    Jones W P: ’On the applied use of human memory models: the memory extender personal filing system’, Int J Man-Machine Studies, 25, pp 191–228 (1986).CrossRefGoogle Scholar
  5. 5.
    Harman D: ’Relevance feedback’, in Frakes W B and Baeza-Yates R (Eds): ‘Information retrieval — data structures and algorithms’, Prentice-Hall, London (1992).Google Scholar
  6. 6.
    Crossley M, Davies N J, Taylor-Hendry R and McGrath A: ’Three-dimensional Internet developments’, BT Technol J, 15, No 2, pp 179–193 (April 1997).CrossRefGoogle Scholar
  7. 7.
    Davies N J, Revett M C and Weeks R: ’Information agents for the World Wide Web’, BT Technol J, 14, No 4, pp 105–114 (October 1996).Google Scholar
  8. 8.
    Davies N J, Revett M C and Weeks R: ’Jasper — communicating information agents’, Proc 4th Intl World Wide Web conference, Boston, USA, also available at (December 1995).
  9. 9.
  10. 10.
  11. 11.
    Frakes W B and Baeza-Yates R (Eds): ‘Information retrieval — data structures and algorithms’, Prentice-Hall, London (1992).Google Scholar
  12. 12.
    Voorhees E M: ’Query expansion using lexical-semantic relations’, Siemens Corporate Research Inc, NJ 08540 (1990).Google Scholar
  13. 13.
    Miller G A: ’WordNet: an on-line lexical database’, International Journal of Lexicography, 3, No 4 (1990).Google Scholar
  14. 14.
    Balabanoviae M and Shoham Y: ’Learning information retrieval agents — experiments with automated Web browsing’, Department of Computer Science, Stanford University, CA 94305 (1996).Google Scholar
  15. 15.
    Simpson P K: ’Artificial neural systems’, Pergamon Press (1990).Google Scholar
  16. 16.
    Jennings A and Higuchi H: ’A personal news service based on a user model neural network’, Kansai Advanced Research Centre, Communications Research Laboratory, Owaoka, Kobe, Japan (1996).Google Scholar
  17. 17.
    Shardanand U: ’Social information filtering for music recommendation’, MIT Media Laboratory, Learning and Common Sense Group, Technical Report 94-04 (1994).Google Scholar
  18. 18.
    Fisk D: ’Recommending films using social filtering’, MSc dissertation (1995).Google Scholar
  19. 19.
    Stewart R S and Davies N J: ’User profiling techniques — a critical review’, Proc 19th Annual BCS Information Retrieval Colloquium, Aberdeen, UK (April 1997).Google Scholar
  20. 20.
    Goldberg D, Nichols D, Oki B and Terry D: ’Using collaborative filtering to weave an information tapestry’, Communications of the ACM, 35, No 12 (1995).Google Scholar
  21. 21.
    Rasmussen E: ’Clustering algorithms’, in Frakes W B and Baeza-Yates R (Eds): ‘Information retrieval — data structures and algorithms’, Prentice-Hall, London (1992).Google Scholar
  22. 22.
    Griffiths A, Robinson L A and Willett P: ’Hierarchic agglomerative clustering methods for automatic document classification’, Journal of Documentation, 40, No 3, pp 175–205 (September 1984).Google Scholar
  23. 23.
    Ruge G: ’Human memory models and term association’, Proc 18th Annual International ACM SIGIR Conference, Washington, USA (1995).Google Scholar
  24. 24.
    Wettler M and Rapp R: ’A connectionist system to simulate lexical decisions in information retrieval’, in Pfeifer R, Schreter Z, Fogelman F and Steels L (Eds): ‘Connectionism in Perspective’, Elsevier, Amsterdam (1989).Google Scholar
  25. 25.
    Chakravarthy A S and Haase K B: ’NetSerf — using semantic knowledge to find Internet information archives’, Proc 18th Annual International ACM SIGIR Conference,Washington, USA (1995).Google Scholar
  26. 26.
    Rada R and Bicknell E: ’Ranking documents based on a thesaurus’, Journal of the American Society for Information Science, 40, No 5, pp 304–310 (1989).CrossRefGoogle Scholar
  27. 27.
    Salton G: ’The SMART Retrieval System’, Prentice-Hall, Englewood Cliffs, NJ (1971).Google Scholar
  28. 28.
  29. 29.
  30. 30.
    Leveridge P C: ’CampusWorld and BT’s on-line education service’, BT Technol J, 15, No 2, pp 126–131 (April 1997).CrossRefGoogle Scholar
  31. 31.
    Rhodes B: ’The Remembrance Agent — a continuously running automated information retrieval system’, Proceedings of The First International Conference on The Practical Application of Intelligent Agents and Multi Agent Technology (PAAM ’96), London, UK, pp 487–495 (April 1996).Google Scholar

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© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  • N. J. Davies
  • M. C. Revett

There are no affiliations available

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