Information Retrieval with a Simplified Conceptual Graph-Like Representation

We argue for that taking into account semantic relations between words in the text can improve information retrieval performance. We implemented the process of information retrieval with simplified Conceptual Graphlike structures and compare the results with those of the vector space model. Our semantic representation, combined with a small simplification of the vector space model, gives better results. In order to build Conceptual Graph-like representation, we have developed a grammar based on the dependency formalism and the standard defined for Conceptual Graphs (CG). We used noun premodifiers and noun post-modifiers, as well as verb frames, extracted from VerbNet, as a source of definition of semantic roles. VerbNet was chosen since its definitions of semantic roles have much in common with the CG standard. We experimented on a subset of the ImageClef 2008 collection of titles and annotations of medical images.

• Type: Journal
• Year: 2010
• Where: MICAI
• Authors: Sonia Ordoñez-Salinas, Alexander F. Gelbukh
• Keywords: Artificial Intelligence, Information Retrieval, MICAI 2010, Semantic, Vector Space Model