Abstract
In order to help to choose similarity or distance measures for information retrieval systems, we compare the orders these measures induce and quantify their agreement by a degree of equivalence. We both consider measures dedicated to binary and numerical data, carrying out experiments both on artificial and real data sets, and identifying equivalent as well as quasi-equivalent measures that can be considered as redundant in the information retrieval framework.
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Lesot, MJ., Rifqi, M. (2010). Order-Based Equivalence Degrees for Similarity and Distance Measures. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Computational Intelligence for Knowledge-Based Systems Design. IPMU 2010. Lecture Notes in Computer Science(), vol 6178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14049-5_3
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DOI: https://doi.org/10.1007/978-3-642-14049-5_3
Publisher Name: Springer, Berlin, Heidelberg
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