Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu


  • Tetsuya SakaiEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_80620


D-measure is a family of evaluation measures for diversified search, where we have a set of known intents (a.k.a. subtopics) {i} for a given topic q and the intent probabilitiesPr(i|q), such that ∑iPr(i|q) = 1. It is assumed that per-intent graded relevance assessments are also available for the topic and that the gain value for each document of relevance l with respect to a particular intent is given by gainl. For example, let the per-intent gain be 3 for a highly relevant document, 2 for a relevant document, and 1 for a partially relevant document. Given a ranked list, let gi(r) = gainl if the document at rank r is l-relevant to intent i, and gi(r) = 0 otherwise. The global gain at r is defined as GG(r) =∑iPr(i|q)gi(r). An ideal list for diversified search is defined by sorting all known relevant documents by the global gain; the global gain at rank r in the ideal list is denoted by GG(r). Then, any graded relevance evaluation measure computed based on GG(r) and GG(r)...

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Waseda UniversityTokyoJapan