Knowledge discovery in musical databases for moods detection

dc.creatorSánchez, P.
dc.creatorCano, J.
dc.creatorGarcía, D.
dc.creatorPinzon, A.
dc.creatorRodriguez, G.
dc.creatorGarcía- González, J.
dc.creatorPerez, L.
dc.date.accessioned2020-04-17T17:09:11Z
dc.date.accessioned2022-11-14T19:57:29Z
dc.date.available2020-04-17T17:09:11Z
dc.date.available2022-11-14T19:57:29Z
dc.date.created2020-04-17T17:09:11Z
dc.date.issued2019-12
dc.identifier15480992
dc.identifierhttps://hdl.handle.net/20.500.12442/5119
dc.identifierhttps://www.inaoep.mx/~IEEElat/index.php/transactions/article/view/2359/362
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5184940
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.
dc.languageeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.sourceIEEE LATIN AMERICA TRANSACTIONS
dc.sourceVol. 17, N°. 12 (2019)
dc.subjectData mining
dc.subjectKnowledge discovery
dc.subjectDatabases process
dc.subjectMusic
dc.subjectPrediction
dc.subjectData Analysis
dc.titleKnowledge discovery in musical databases for moods detection
dc.typearticle


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