Association measures and aggregation functions

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

13 Scopus citations

Abstract

The concept of association measure generalizing the Pearson correlation coefficient is introduced. The methods of generation of association measures by means of pseudo-difference associated to some t-conorm and by similarity measures are proposed. The association measure can be introduced on any set with involutive reflection operation and suitably defined similarity measure. The methods of construction of association measures by Minkowski metric and data standardization using the aggregation functions are considered. The cosine similarity and the Pearson's correlation coefficient are obtained as partial cases of the proposed general methods.

Original languageEnglish
Title of host publicationAdvances in Soft Computing and Its Applications - 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Proceedings
Pages194-203
Number of pages10
EditionPART 2
DOIs
StatePublished - 2013
Externally publishedYes
Event12th Mexican International Conference on Artificial Intelligence, MICAI 2013 - Mexico City, Mexico
Duration: 24 Nov 201330 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8266 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Mexican International Conference on Artificial Intelligence, MICAI 2013
Country/TerritoryMexico
CityMexico City
Period24/11/1330/11/13

Keywords

  • Association measure
  • Correlation coefficient
  • Cosine similarity
  • Data standardization
  • Idempotence
  • Involutivity
  • Minkowski distance
  • Pseudo-difference
  • Reflection
  • Similarity measure
  • T-conorm

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