The focus of my PhD is on the use of Semantic Web technologies to enhance Recommender Systems. In particular, I focus on gathering information from different Linked Data and unstructured sources to improve the description of the items to recommend. I focus mainly on media items (e.g., TV programmes) which I enrich using DBpedia, IMDB, review websites, and other Web sources. I employ SWI-Prolog and Python as programming language.
My Research Proposal entitled Burst the Filter Bubble: Using Semantic Web to Enable Serendipity is available here.
My MSc thesis about the analysis between Social Networks and TV Audience entitled Online TV Buzz is available here.
My curriculum is available here.