Semantic Web and Knowledge Representation for User Modelling and Content Recommendation

Felipe Cueto
Rubén Manrique

Any digital document available on the web carries knowledge. In this project, we extract and structure the embedded knowledge of these resources, link them with Semantic Web Knowledge Graphs and reason with the explicit recovered knowledge to solve problems such as intelligent Web search, semantic query reformulation, document comparison, etc. Moreover, applying these same techniques to users’ profiles, interests, and knowledge, we can do intelligent semantic-based user-centered recommendations.


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