| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560768 |
| ISSN: | 1405-5546 |
| Autores: | Satornicio Medina, Andrés Leonardo1 Sucari León, Reynaldo2 Calderón Vilca, Hugo D.1 |
| Instituciones: | 1Universidad Nacional Mayor de San Marcos, Lima, Lima. Perú 2Universidad Nacional Autónoma de Huanta, Ayacucho. Perú |
| Año: | 2023 |
| Periodo: | Ene-Mar |
| Volumen: | 27 |
| Número: | 1 |
| Paginación: | 53-62 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | 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. |
| Keyword: | Natural language processing, Neural networks, Sentiment analysis, Music recommendation |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
