Towards a context sensitive approach to searching information based on domain specific knowledge sources

In the context of document retrieval in the biomedical domain, this paper introduces a novel approach to searching for biomedical information using contextual semantic information. More specifically, we propose to combine the contextual semantic information in documents and user queries in an attempt to improve the performance of biomedical information retrieval (IR) systems. Contextual information provides knowledge about a domain in a global context or statistical properties of a sub collection of documents related to a given query in a local context. In our context sensitive IR approach, terms denoting concepts are extracted from each document using several biomedical terminologies. Preferred terms denoting concepts are used to enrich the semantics of the document content via document expansion. The user query is expanded using terms extracted from the top-ranked expanded documents via a blind feedback query expansion approach. In addition, we aim to evaluate the utility of incorporating several terminologies within the proposed context sensitive approach. The experiments carried out on the TREC Genomics 2004 and 2005 test sets show that our context-sensitive IR approach significantly outperforms state-of-the-art baseline approaches.