Exploring the benefit of contextual information for boosting TREC Genomic IR performance

Abstract Query Expansion is a widely used technique that augments a query with synonymous and related terms in order to address a common issue in ad hoc retrieval: the vocabulary mismatch problem, where relevant documents contain query terms that are semantically similar, but lexically distinct. Standard query expansion techniques include pseudo relevance feedback and ontology-based expansion. In this paper, we explore the use of contextual information as a means of expanding the context surrounding the unit of retrieval, rather than the query, which in this case is a document passage. The ad hoc retrieval task that we focus on in this paper was investigated at the TREC 2006 Genomic tracks, where systems were required to retrieve relevant answer passages. The most commonly reported indexing strategy was passage indexing. Although this simplifies post-retrieval processing, retrieval performance can be hurt as valuable contextual information in the containing document is lost. The focus of this paper is to investigate various contextual evidence of similarity outside of the passage such as: query/full-text similarity, query/citation sentence similarity, query/title similarity, query/abstract similarity. These similarity scores are then used to boost the rank of passages that exhibit high contextual evidence of query similarity. Our experimental results suggest that document context provides the strongest evidence of contextual information for this task