INVESTIGADORES
ACIAR Silvana Vanesa
congresos y reuniones científicas
Título:
Comparing product specifications to solve the cold start problem in a recommender system
Autor/es:
SILVANA ACIAR; GABRIELA ACIAR; DEBBIE ZHANG
Lugar:
Valparaiso
Reunión:
Congreso; Computing Conference (CLEI), 2016 XLII Latin American; 2016
Resumen:
Recommender systems are widely used applications to solve the problems of information overload, usually on websites. A well-known problem of recommender systems is the problem of cold start, which is caused by the lack of data. A recommendation system can only produce good recommendations after it has accumulated enough data The problem becomes even more challenging when the recommender system comes to deal with new products or the products have not been evaluated by consumers. This paper addresses this problem based on a comparison of product specifications, experiments were conducted in the recommendation domain of digital cameras.