Multiplying Concept Sources for Graph Modeling

This paper presents the LIG contribution to the CLEF 2007 medical retrieval task (i.e. ImageCLEFmed). The main idea in this paper is to incorporate medical knowledge in the language modeling approach to information retrieval (IR). Our model makes use of the textual part of ImageCLEFmed corpus and of the medical knowledge as found in the Unified Medical Language System (UMLS) knowledge sources. The use of UMLS allows us to create a conceptual representation of each sentence in the corpus. We use these sentence representations to create a graph model for each document. As in the standard language modeling approach, we evaluate the probability that a document graph model generates the query graph. Graphs are created from medical texts and queries, and are built for different languages, with different methods. The use of a conceptual representation allows the system to work at a higher semantic level, which solves some of the information retrieval problems, as term variation. After dev...

• Type: Conference
• Year: 2007
• Where: CLEF
• Authors: Loïc Maisonnasse, Éric Gaussier, Jean-Pierre Chevallet
• Keywords: CLEF 2007, Graph Model, Information Retrieval, Language Modeling Approach