MOOD-TUNES: Music Recommendation System Based on People's Facial Expressions

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dc.contributor.advisorShahriar Hussain
dc.contributor.authorJisan Ahmed
dc.contributor.authorRubaiyet Arefin Oishi
dc.contributor.authorSajadul Islam Akash
dc.contributor.authorAkil Hossain Prottoy
dc.contributor.id2011135042
dc.contributor.id1921585042
dc.contributor.id1831722642
dc.contributor.id1931795642
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-07-23
dc.date.accessioned2025-07-23T04:58:28Z
dc.date.available2025-07-23T04:58:28Z
dc.date.issued2023
dc.description.abstractMusic recommendation systems have become increasingly popular and important in recent years. These systems utilize user behavior analysis, preferences, and historical data to provide personalized music recommendations. However, existing approaches predominantly rely on explicit user feedback, such as ratings, playlists, or browsing history, which may not always accurately reflect users' true preferences. Furthermore, these systems often overlook the significance of non-verbal cues and emotional responses in shaping users' music preferences.
dc.description.degreeUndergraduate
dc.identifier.cd600000812
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1315
dc.language.isoen
dc.publisherNorth South University
dc.rights©Nsulibrary
dc.titleMOOD-TUNES: Music Recommendation System Based on People's Facial Expressions
dc.typeProject
oaire.citation.endPage46
oaire.citation.startPage1
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