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Evaluating Hierarchical Clustering of Search Results

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String Processing and Information Retrieval (SPIRE 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3772))

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Abstract

We propose a goal-oriented evaluation measure, Hierarchy Quality, for hierarchical clustering algorithms applied to the task of organizing search results -such as the clusters generated by Vivisimo search engine-. Our metric considers the content of the clusters, their hierarchical arrangement, and the effort required to find relevant information by traversing the hierarchy starting from the top node. It compares the effort required to browse documents in a baseline ranked list with the minimum effort required to find the same amount of relevant information by browsing the hierarchy (which involves examining both documents and node descriptors).

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References

  1. Carpineto, C., Romano, G.: Concept Data Analysis. Data and Applications. Wiley, Chichester (2004)

    Book  Google Scholar 

  2. Cigarran, J., Gonzalo, J., Peñas, A., Verdejo, F.: Browsing search results via formal concept analysis: Automatic selection of attributes. In: Eklund, P. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 74–87. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  3. Cigarran, J., Peñas, A., Gonzalo, J., Verdejo, F.: Automatic selection of noun phrases as document descriptors in an fca-based information retrieval system. In: Formal Concept Analysis. Springer, Heidelberg (2005)

    Google Scholar 

  4. Ferragina, P., Gulli, A.: A personalized search engine based on web-snippet hierarchical clustering. In: WWW 2005: Special interest tracks and posters of the 14th international conference on World Wide Web, pp. 801–810. ACM Press, New York (2005)

    Chapter  Google Scholar 

  5. Hearst, M., Pedersen, J.: Reexamining the cluster hypothesis: Scatter/gather on retrieval results. In: Proceedings of SIGIR-96, 19th ACM International Conference on Research and Development in Information Retrieval, Zurich, CH, pp. 76–84 (1996)

    Google Scholar 

  6. Kummamuru, K., Lotlikar, R., Roy, S., Singal, K., Krishnapuram, R.: A hierarchical monothetic document clustering algorithm for summarization and browsing search results. In: WWW 04: Proceedings of the 13th international conference on World Wide Web, pp. 658–665. ACM Press, New York (2004)

    Chapter  Google Scholar 

  7. Lawrie, D., Croft, W.: Discovering and comparing topic hierarchies. In: Proceedings of RIAO 2000 (2000)

    Google Scholar 

  8. Leouski, A., Croft, W.: An evaluation of techniques for clustering search results (1996)

    Google Scholar 

  9. Rose, D.E., Levinson, D.: Understanding user goals in web search. In: WWW 2004: Proceedings of the 13th international conference on World Wide Web, pp. 13–19. ACM Press, New York (2004)

    Chapter  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Cigarran, J.M., Pen̈as, A., Gonzalo, J., Verdejo, F. (2005). Evaluating Hierarchical Clustering of Search Results. In: Consens, M., Navarro, G. (eds) String Processing and Information Retrieval. SPIRE 2005. Lecture Notes in Computer Science, vol 3772. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11575832_7

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  • DOI: https://doi.org/10.1007/11575832_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29740-6

  • Online ISBN: 978-3-540-32241-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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