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Knowledge discovery in musical databases for moods detection

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dc.contributor.authorSánchez, P.
dc.contributor.authorCano, J.
dc.contributor.authorGarcía, D.
dc.contributor.authorPinzon, A.
dc.contributor.authorRodriguez, G.
dc.contributor.authorGarcía- González, J.
dc.contributor.authorPerez, L.
dc.date17-04-2050spa
dc.date.accessioned2020-04-17T17:09:11Z
dc.date.available2020-04-17T17:09:11Z
dc.date.issued2019-12
dc.description.abstractIn this paper, methodology Knowledge discovery in databases is used in the design and implementation of a tool for moods detection from musical data. The application allows users to interact with a music player, and based on their playlist and musical genre, recognizes and classified their emotional state using a neural network. The results found are promising to have an accuracy of more than 72,4%, in addition the developed tool allows the constant taking and storage of data, the analysis in real time and issues suggestions of songs to positively influence the current emotional state, so that a greater use of the application can guarantee better results.spa
dc.format.mimetypepdfspa
dc.identifier.issn15480992spa
dc.identifier.urihttps://hdl.handle.net/20.500.12442/5119
dc.identifier.urlhttps://www.inaoep.mx/~IEEElat/index.php/transactions/article/view/2359/362
dc.language.isoengspa
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)spa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacionaleng
dc.rights.accessrightsinfo:eu-repo/semantics/closedAccessspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceIEEE LATIN AMERICA TRANSACTIONSeng
dc.sourceVol. 17, N°. 12 (2019)spa
dc.subjectData miningeng
dc.subjectKnowledge discoveryeng
dc.subjectDatabases processeng
dc.subjectMusiceng
dc.subjectPredictioneng
dc.subjectData Analysiseng
dc.titleKnowledge discovery in musical databases for moods detectionspa
dc.typearticlespa
dc.type.driverarticlespa
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