Information Recovery and Discovery in Collaborative Web Search

  • Maurice Coyle
  • Barry Smyth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4425)


When we search for information we are usually either trying to recover something that we have found in the past or trying to discover some new information. In this paper we will evaluate how the collaborative Web search technique, which personalizes search results for communities of like-minded users, can help in recovery-and discovery-type search tasks in a corporate search scenario.


Search Session Exploratory Search Discovery Task Information Recovery Search History 
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.
    Bharat, K.: SearchPad: Explicit Capture of Search Context to Support Web Search. In: Proceedings of the Ninth International World-Wide Web Conference (WWW ’00), pp. 493–501. North-Holland, Amsterdam (2000)Google Scholar
  2. 2.
    Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30(1–7), 107–117 (1998)CrossRefGoogle Scholar
  3. 3.
    Budzik, J., Hammond, K.: User Interactions with Everyday Applications as Context for Just-In-Time Information Access. In: Proceedings of the 3rd International Conference on Intelligent User Interfaces (IUI ’00), pp. 44–51. ACM Press, New York (2000)CrossRefGoogle Scholar
  4. 4.
    Coyle, M., Smyth, B.: On the Community-Based Explanation of Search Results. In: Proceedings of the 10th International Conference on Intelligent User Interfaces (IUI ’07), Hawaii, U.S.A, ACM Press, New York (2007)Google Scholar
  5. 5.
    Feldman, S., Sherman, C.: The High Cost of Not Finding Information. In: (IDC White Paper), IDC Group (2000)Google Scholar
  6. 6.
    Finkelstein, L., et al.: Placing search in context: the concept revisited. In: Proceedings of the 10th International Conference on the World Wide Web (WWW ’01), Hong Kong, pp. 406–414. ACM Press, New York (2001), CrossRefGoogle Scholar
  7. 7.
    Capra III., R.G., Pérez-Quiñones, M.A.: Using web search engines to find and refind information. Computer 38(10), 36–42 (2005)CrossRefGoogle Scholar
  8. 8.
    Glover, E., et al.: Web Search - Your Way. Communications of the ACM 44(12), 97–102 (2000)CrossRefGoogle Scholar
  9. 9.
    Marchionini, G.: Exploratory search: from finding to understanding. Communications of the ACM 49(4), 41–46 (2006), doi:10.1145/1121949.1121979CrossRefGoogle Scholar
  10. 10.
    O’Day, V.L., Jeffries, R.: Orienteering in an information landscape: how information seekers get from here to there. In: Proceedings of the SIGCHI conference on Human factors in computing systems (CHI ’93), Amsterdam, The Netherlands, pp. 438–445. ACM Press, New York (1993), doi:10.1145/169059.169365CrossRefGoogle Scholar
  11. 11.
    Silverstein, C., et al.: Analysis of a Very Large AltaVista Query Log. Technical Report 1998-014, Digital SRC (1998)Google Scholar
  12. 12.
    Smyth, B., et al.: A Live-user Evaluation of Collaborative Web Search. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI ’05), Edinburgh, Scotland, pp. 1419–1424. Morgan Kaufmann, San Francisco (2005)Google Scholar
  13. 13.
    Smyth, B., et al.: Exploiting query repetition and regularity in an adaptive community-based web search engine. User Modeling and User-Adapted Interaction: The Journal of Personalization Research 14(5), 383–423 (2004)CrossRefGoogle Scholar
  14. 14.
    Teevan, J., et al.: History repeats itself: repeat queries in yahoo’s logs. In: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR ’06), Seattle, Washington, USA, pp. 703–704. ACM Press, New York (2006), doi:10.1145/1148170.1148326CrossRefGoogle Scholar
  15. 15.
    Wexelblat, A., Maes, P.: Footprints: History-Rich Web Browsing.. In: Proceedings of the Third International Conference on Computer-Assisted Information Retrieval (RIAO ’97), Montreal, Quebec, Canada, pp. 75–84 (1997)Google Scholar
  16. 16.
    White, R.W., et al.: Supporting exploratory search. Communications of the ACM Special Issue 49(4) (2006)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Maurice Coyle
    • 1
  • Barry Smyth
    • 1
  1. 1.Adaptive Information Cluster, School of Computer Science & Informatics, University College Dublin, Belfield, Dublin 4Ireland

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