A Guide to Similarity Measures

Avivit Levy; B. Riva Shalom; Michal Chalamish

A Guide to Similarity Measures

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arxiv 2408.07706 v1 pith:PEMBCWPU submitted 2024-08-07 cs.IR cs.CVcs.LG

Avivit Levy , B. Riva Shalom , Michal Chalamish This is my paper · ORCID

classification cs.IRcs.CVcs.LG

keywords measuressimilarityapplicationfindguidemeasurenon-expertsassortment

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Similarity measures play a central role in various data science application domains for a wide assortment of tasks. This guide describes a comprehensive set of prevalent similarity measures to serve both non-experts and professional. Non-experts that wish to understand the motivation for a measure as well as how to use it may find a friendly and detailed exposition of the formulas of the measures, whereas experts may find a glance to the principles of designing similarity measures and ideas for a better way to measure similarity for their desired task in a given application domain.

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