Knowledge discovery in musical databases for moods detection
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Fecha
2019-12
Autores
Sánchez, P.
Cano, J.
García, D.
Pinzon, A.
Rodriguez, G.
García- González, J.
Perez, L.
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Editor
Institute of Electrical and Electronics Engineers (IEEE)
Resumen
In 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.
Descripción
Palabras clave
Data mining, Knowledge discovery, Databases process, Music, Prediction, Data Analysis