A guide to similarity measures and their data science applications
Avivit Levy, B. Riva Shalom, Michal Chalamish
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 professionals. 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.
Topics & Concepts
Computational Science and EngineeringComputer scienceSimilarity (geometry)Data scienceInformation retrievalData miningArtificial intelligenceMachine learningImage (mathematics)Time Series Analysis and ForecastingImage Retrieval and Classification TechniquesAnomaly Detection Techniques and Applications