Music Recommender System based on Sentiment Analysis Enhanced with Natural Language Processing Technics

Authors

  • Hugo David Calderon Vilca Universidad Nacional Mayor de San Marcos - Perú
  • Andres Leonardo Satornicio Medina Universidad Nacional Mayor de San Marcos - Perú
  • Reynaldo Sucari Leon Universidad Nacional Mayor de San Marcos - Perú

DOI:

https://doi.org/10.13053/cys-27-1-4006

Keywords:

Natural language processing, neural networks, sentiment analysis, music recommendation

Abstract

In the field of computer science, many efforts have been made with respect to music recommendation in order to offer the user songs much more in line with his current context or tastes and thus also reduce the large number of musical pieces found on the web. However, there are few studies that take into account the user’s feelings for this task. In this paper we present a model and recommendation system that emphasizes sentiment analysis to make music recommendations using natural language processing, this is achieved by using different artificial intelligence tools such as Word2Vec to vectorize words and neural networks to recognize the sentimental information of the texts. In the results, we show that this approach improves the recommendation results obtained by 80% for the accuracy metrics.

Author Biographies

Hugo David Calderon Vilca, Universidad Nacional Mayor de San Marcos - Perú

* Profesor de la Universidad Nacional Mayor de San Marcos UNMSM, cursos que dicta: Redes Neuronales, Inteligencia Artificial y Tesis. * Profesor de la Universidad Peruana de Ciencias Aplicadas UPC, cursos que dicta: Inteligencia Artificial y Seminario de Investigación Científica. * Dedicado a la investigación científica en la disciplina Inteligencia Artificial en el área de Aprendizaje Máquina y Procesamiento de Lenguaje Natural. EXPERIENCIA: * Docente de la maestría en Informática de la Universidad Nacional del Altiplano Puno UNAP. * Director de Investigación de la Universidad Nacional Micaela Bastidas de Apurímac UNAMBA. * Coordinador de la Maestría en Informática Sede Abancay de la UNAP. * Director de Escuela Académica Profesional de Ingeniería Informática y Sistemas de la UNAMBA. * Jefe de la Oficina de Tecnologías de la Información de la UNAMBA. * Docente Pre grado de la UNAMBA. * Docente Pre grado de la Universidad Tecnológica de los Andes UTEA.

Andres Leonardo Satornicio Medina, Universidad Nacional Mayor de San Marcos - Perú

Experto en ingeniería de software, profundización inteligencia artificial.Procesamiento de lenguaje natural

Reynaldo Sucari Leon, Universidad Nacional Mayor de San Marcos - Perú

Docente Principal en la Universidad Nacional Autónoma de Huanta, Director del Instituto de Investigación de la UNAH, Coordinador del Grupo de Investigación en Tecnología Aplicada de la UNAH, miembro del Instituto de Investigación en Ciencias de la Computación de la EPG-UNAP, Tutor Virtual en el MINEDU área Matemática y Tecnología Informática, docente de post grado (Doctorado, Maestría y Seg. Especialidad) en la Universidad Nacional Mayor de San Marcos, Universidad Nacional del Altiplano y Universidad César Vallejo, docente invitado en diversas universidades del Perú, especialista en investigación cuantitativa, asesor, consultor y docente de estadística. Programador de software a medida para diversas instituciones. Temas de interés: Modelamiento matemático y estadístico, control de calidad, Inteligencia artificial, problemas de enseñanza-aprendizaje y administración educativa.

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Published

2023-03-30

Issue

Vol. 27 No. 1 (2023): 27(1) 2023

Section

Articles

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