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). © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Cigarran, J. M., Peñas, A., Gonzalo, J., & Verdejo, F. (2005). Evaluating hierarchical clustering of search results. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3772 LNCS, pp. 49–54). https://doi.org/10.1007/11575832_7
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