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• W2790865082 abstract "For the evaluation of diversified search results, a number of different methods have been proposed in the literature. Prior to making use of such evaluation methods, it is important to have a good understanding of how diversity and relevance contribute to the performance metric of each method. In this paper, we use the statistical technique ANOVA to analyse and compare three representative evaluation methods for diversified search, namely (alpha )-nDCG, MAP-IA, and ERR-IA, on the TREC-2009 Web track dataset. It is shown that the performance scores provided by those evaluation methods can indeed reflect two crucial aspects of diversity — richness and evenness — as well as relevance, though to different degrees." @default.
• W2790865082 created "2018-03-29" @default.
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• W2790865082 date "2018-01-01" @default.
• W2790865082 modified "2023-10-16" @default.
• W2790865082 title "A Meta-Evaluation of Evaluation Methods for Diversified Search" @default.
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• W2790865082 doi "https://doi.org/10.1007/978-3-319-76941-7_43" @default.
• W2790865082 hasPublicationYear "2018" @default.
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