Ontology-Based Advertisement Recommendation in Social Networks.

With the advent of the Web 2.0 era, a new source of a vast amount of data about users become available. Advertisement recommendation systems are among the applications that can benefit from these data since they can help gain a better understanding of the users' interests and preferences. However, new challenges emerge from the need to deal with heterogeneous data from disparate sources. Semantic technologies, in general, and ontologies, in particular, have proved effective for knowledge management and data integration. In this work, an ontology-based advertisement recommendation system that leverages the data produced by users in social networking sites is proposed.