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A Guide to Similarity Measures

Authors :
Levy, Avivit
Shalom, B. Riva
Chalamish, Michal
Publication Year :
2024

Abstract

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.<br />Comment: 27 pages

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2408.07706
Document Type :
Working Paper