The Quest for Information Retrieval on the Semantic Web

Abstract. Semantic search has been one of the motivations of the Semantic Web since it was envisioned. In my thesis I research the development of a new retrieval model for the exploitation of ontology-based KBs (Knowledge Bases) to improve search over large document repositories. In my current approach I consider an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. In this approach, semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness. The method has been tested on corpora of significant size, showing promising results respect to keyword-based search, and providing ground for further analysis and research.