A Guide to Similarity Measures
<|reference_start|>A Guide to Similarity Measures: 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.<|reference_end|>
@article{levy2024a,
    title={A Guide to Similarity Measures},
    author={Avivit Levy, B. Riva Shalom and Michal Chalamish},
    journal={arXiv preprint arXiv:2408.07706},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.07706},
    primaryClass={cs.IR cs.CV cs.LG}
}