How to select an appropriate similarity measure: Towards a symmetry-based approach

Ildar Batyrshin, Thongchai Dumrongpokaphan, Vladik Kreinovich, Olga Kosheleva

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

When practitioners analyze the similarity between time series, they often use correlation to gauge this similarity. Sometimes this works, but sometimes, this leads to counter-intuitive results, in which case other similarity measures are more appropriate. An important question is how to select an appropriate similarity measures. In this paper, we show, on simple examples, that the use of natural symmetries – scaling and shift – can help with such a selection.

Original languageEnglish
Title of host publicationIntegrated Uncertainty in Knowledge Modelling and Decision Making - 5th International Symposium, IUKM 2016, Proceedings
EditorsBac Le, Bao Nguyen Le, Thierry Denoeux, Van-Nam Huynh, Masahiro Inuiguchi
PublisherSpringer Verlag
Pages457-468
Number of pages12
ISBN (Print)9783319490458
DOIs
StatePublished - 2016
Event5th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2016 - Da Nang, Viet Nam
Duration: 30 Nov 20162 Dec 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9978 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2016
Country/TerritoryViet Nam
CityDa Nang
Period30/11/162/12/16

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