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Clustering-Based Visual Interfaces for Presentation of Web Search Results: An Empirical Investigation

Author

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  • Ozgur Turetken

    (Temple University)

  • Ramesh Sharda

    (Oklahoma State University)

Abstract

The result of a typical web search is often overwhelming. It is very difficult to explore the textual listing of the resulting documents, which may be in the thousands. In order to improve the utility of the search experience, we explore presenting search results through clustering and a zoomable two-dimensional map (zoomable treemap). Furthermore, we apply the fisheye view technique to this map of web search clusters to provide details in context. In this study, we report on our evaluation of these presentation features. The particular interfaces evaluated were: (1) a textual list, (2) a zoomable two-dimensional map of the clustered results, and (3) a fisheye version of the zoomable two-dimensional map where the results were clustered. We found that subjects completed search tasks faster with the visual interfaces than with the textual interface, and faster with the fisheye interface than just the zoomable interface. Based on the findings, we conclude that there is promise in the use of clustering and visualization with a fisheye zooming capability in the exploration of web search results.

Suggested Citation

  • Ozgur Turetken & Ramesh Sharda, 2005. "Clustering-Based Visual Interfaces for Presentation of Web Search Results: An Empirical Investigation," Information Systems Frontiers, Springer, vol. 7(3), pages 273-297, July.
    • Handle: RePEc:spr:infosf:v:7:y:2005:i:3:d:10.1007_s10796-005-2770-7
    DOI: 10.1007/s10796-005-2770-7
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    References listed on IDEAS

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    1. Jacoby, Jacob, 1984. "Perspectives on Information Overload," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(4), pages 432-435, March.
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    Cited by:

    1. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    2. Lin-Chih Chen, 0. "Interactive Topic Search System Based on Topic Cluster Technology," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    3. Lin-Chih Chen, 2021. "Interactive Topic Search System Based on Topic Cluster Technology," Information Systems Frontiers, Springer, vol. 23(5), pages 1227-1243, September.

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