Abstract
A current strategy for improving sales as well as customer satisfaction in the e-commerce field is to provide product recommendation to users. The increasing acceptance of web recommender systems is mainly due to the advances achieved in the intensive research carried out for several years. However, in spite of these improvements, recommender systems still present some important drawbacks that prevent from satisfying entirely their users. In this work, a methodology that combines an association rule mining method with the definition of a domain-specific ontology is proposed in order make efficient book recommendations.
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Asjana, M., López, V.F., Muñoz, M.D., Moreno, M.N. (2012). Semantic Web Mining for Book Recommendation. In: Casillas, J., Martínez-López, F., Corchado Rodríguez, J. (eds) Management Intelligent Systems. Advances in Intelligent Systems and Computing, vol 171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30864-2_10
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DOI: https://doi.org/10.1007/978-3-642-30864-2_10
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