Collaborative Recommender System Based on Improved Firefly Algorithm
Título del documento: Collaborative Recommender System Based on Improved Firefly Algorithm
Revista: Computación y sistemas
Base de datos:
Número de sistema: 000560676
ISSN: 1405-5546
Autores: 1
2
3
4
Instituciones: 1Maharaja Surajmal Institute of Technology, Department of Information Technology, Delhi. India
2Maharaja Surajmal Institute of Technology, Department of Computer Science and Engineering, Delhi. India
3Bhagwan Parshuram Institute of Technology, Department of Computer Science and Engineering, Delhi. India
4Netaji Subhas University of Technology, Department of Computer Science and Engineering, Delhi. India
Año:
Periodo: Abr-Jun
Volumen: 26
Número: 2
Paginación: 537-549
País: México
Idioma: Inglés
Tipo de documento: Artículo
Resumen en inglés A recommendation system aims to capture the taste of the customer and predict relevant items which he/she may be interested in buying. There are many algorithms for generating recommendations in literature, however, most of them are non-optimal and do not have the capability to handle big data. In this paper, a collaborative recommendation system is proposed based on improved firefly algorithm. The firefly algorithm is used to generate optimal clusters which provide effective recommendations. The proposed algorithm works in two phases: Phase I which generates the clusters with firefly algorithm and Phase II gives real time recommendations. The firefly algorithm has been implemented in Apache Spark to give it the capability of handling big data. The combination of improved firefly-based clustering and Apache Spark makes it much faster and optimal than the state-of-the-art recommendation models. For experiments, movie-lens dataset has been utilized and different evaluation metrics have been used for performance analysis. The results show that the proposed method gives better results compared to existing methods.
Disciplinas: Ciencias de la computación
Palabras clave: Inteligencia artificial
Keyword: Artificial intelligence
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