Abstract
We present an extension to knowledge discovery in Music Information Retrieval (MIR) databases and the emotional indices associated with (i) various scalar theory, and (ii) correlative behavioral demographics. Certain societal demographics are set in their ways as to how they dress, behave in society, solve problems and deal with anger and other emotional states. It is also well documented that particular musical scales evoke particular states of emotion and personalities of their own. This paper extends the work that Knowledge Discovery in Databases (KDD) and Rough Set Theory has opened in terms of mathematically linking music scalar theory to emotions. We now, extend the paradigm by associating emotions, based from music, to societal demographics and how strong these relationships to music are as to affect, if at all, how one may dress, behave in society, solve problems and deal with anger and other emotional states.
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Lewis, R., Bihn, M., Mello, C. (2015). Machine Intelligence: The Neuroscience of Chordal Semantics and Its Association with Emotion Constructs and Social Demographics. In: Esposito, F., Pivert, O., Hacid, MS., Rás, Z., Ferilli, S. (eds) Foundations of Intelligent Systems. ISMIS 2015. Lecture Notes in Computer Science(), vol 9384. Springer, Cham. https://doi.org/10.1007/978-3-319-25252-0_32
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DOI: https://doi.org/10.1007/978-3-319-25252-0_32
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