Record number :
Title of article :
Social knowledge-based recommender system. Application to the movies domain
Author/Authors :
Carrer-Neto، نويسنده , , Walter and Hernلndez-Alcaraz، نويسنده , , Marيa Luisa and Valencia-Garcيa، نويسنده , , Rafael and Garcيa-Sلnchez، نويسنده , , Francisco، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Pages :
From page :
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Abstract :
With the advent of the Social Web and the growing popularity of Web 2.0 applications, recommender systems are gaining momentum. The recommendations generated by these systems aim to provide end users with suggestions about information items, social elements, products or services that are likely to be of their interest. The traditional syntactic-based recommender systems suffer from a number of shortcomings that hamper their effectiveness. As semantic technologies mature, they provide a consistent and reliable basis for dealing with data at the knowledge level. Adding semantically empowered techniques to recommender systems can significantly improve the overall quality of recommendations. In this work, a hybrid recommender system based on knowledge and social networks is presented. Its evaluation in the cinematographic domain yields very promising results compared to state-of-the-art solutions.
Keywords :
Recommender Systems , ontologies , Knowledge-based systems , SEMANTIC WEB
Journal title :
Expert Systems with Applications
Serial Year :
Link To Document :