Combining Global and Local Semantic Contexts for Improving Biomedical Information Retrieval

In the context of biomedical information retrieval (IR), this paper explores the relationship between the document’s global context and the query’s local context in an attempt to overcome the term mismatch problem between the user query and documents in the collection. Most solutions to this problem have been focused on expanding the query by discovering its context, either global or local. In a global strategy, all documents in the collection are used to examine word occurrences and relationships in the corpus as a whole, and use this information to expand the original query. In a local strategy, the top-ranked documents retrieved for a given query are examined to determine terms for query expansion. We propose to combine the document’s global context and the query’s local context in an attempt to increase the term overlap between the user query and documents in the collection via document expansion (DE) and query expansion (QE). The DE technique is based on a statistical meth...

• Type: Journal
• Year: 2011
• Where: ECIR
• Authors: Duy Dinh, Lynda Tamine
• Keywords: Concept Extraction, Document Expansion, ECIR 2011, Information Technology, Word Occurrences