Measurement, selection, and visualization of association rules: A compositional data perspective: A Compositional Data perspective on Association Rules
dc.contributor.author
dc.date.accessioned
2021-07-28T06:54:06Z
dc.date.available
2021-07-28T06:54:06Z
dc.date.issued
2022-04
dc.identifier.issn
0748-8017
dc.identifier.uri
dc.description.abstract
Association rule mining is a powerful data analytic technique used for extracting information from transaction databases with a collection of itemsets. The aim is to indicate what item goes with what item (ie, an association rule) in a set of collected transactions. It is extensively used in text analytics of text records or social media. Here we use Compositional Data analysis (CoDa) techniques to generate new visualizations and insights from association rule mining. These CoDa methods show the relationship between itemsets, their strength, and direction of dependency. Moreover, after expressing each association rule as a contingency table, we discuss two statistical tests to guide identification of the relevant rules by analyzing the relative importance of the elements of the table. As an example, we use these visualizations and statistical tests for investigating the association of negative mood emotions to various types of headache/migraine events. Data for those analysis comes from N1-HeadacheTM, a digital platform where individual users record attacks and symptoms as well as their daily exposure to a list of potential factors
dc.description.sponsorship
This research has been supported by theSpanish Ministry of Economy, Industry and Competitiveness under the project CODAMET (Ref: RTI2018-095518-B-C21)
Open Access funding provided thanks to the CRUE-CSIC agreement with Wiley
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Wiley
dc.relation
RTI2018-095518-B-C21
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Reproducció digital del document publicat a: https://doi.org/10.1002/qre.2910
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Quality and Reliability Engineering International, 2022, vol. 38, núm. 3, p. 1327-1339
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Articles publicats (D-IMA)
dc.rights
Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri
dc.title
Measurement, selection, and visualization of association rules: A compositional data perspective: A Compositional Data perspective on Association Rules
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.relation.projectID
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095518-B-C21/ES/METODOS DEL ANALISIS COMPOSICIONAL DE DATOS/
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
033484
dc.contributor.funder
dc.type.peerreviewed
peer-reviewed
dc.relation.FundingProgramme
dc.relation.ProjectAcronym
dc.identifier.eissn
1099-1638