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Neural Approaches to Decode Semantic Similarities in Spanish Song Lyrics for Enhanced Recommendation Systems

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dc.contributor.advisorFresno Fernandez, Victor
dc.contributor.advisorBenito Santos, Alejandro
dc.contributor.authorGhajari Espinosa, Adrián
dc.date.accessioned2024-09-05T10:05:20Z
dc.date.available2024-09-05T10:05:20Z
dc.date.issued2024-02
dc.description.abstractThis dissertation explores the enhancement of music recommendation systems by integrating semantic similarity in Spanish song lyrics, utilizing advancements in machine learning and natural language processing (NLP), including both supervised and unsupervised approaches. It addresses the gap in current recommendation practices, which often overlook the rich semantic content of lyrics, despite their potential to significantly personalize music recommendations. Through theoretical insights into word embeddings and transfer learning, the development of the LyricSIM dataset for assessing lyric similarity, and empirical evaluations of models designed to distinguish between similar and non-similar song pairs, this research proposes a novel, lyrics-driven approach to music recommendation. Focused on the Spanish-speaking market, where Latin music is prevalent, this study contributes to the field by demonstrating how NLP technologies can refine music recommendations, addressing challenges like the cold start problem and enhancing the diversity of music recommendations, thereby offering a more personalized and engaging user experience in the streaming era.es
dc.identifier.citationGhajari Espinosa, Adrián (2024) Neural Approaches to Decode Semantic Similarities in Spanish Song Lyrics for Enhanced Recommendation Systems. Trabajo fin de máster. Universidad de Educación a Distancia (UNED)
dc.identifier.urihttps://hdl.handle.net/20.500.14468/23613
dc.language.isoes
dc.publisherUniversidad de Educación a Distancia (UNED)
dc.relation.centerFacultades y escuelas::E.T.S. de Ingeniería Informática
dc.relation.degreeMáster universitario en Tecnologías del Lenguaje
dc.relation.departmentLenguajes y Sistemas Informáticos
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject12 Matemáticas::1203 Ciencia de los ordenadores ::1203.17 Informática
dc.titleNeural Approaches to Decode Semantic Similarities in Spanish Song Lyrics for Enhanced Recommendation Systemses
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dc.typemaster thesisen
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