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In this paper, we propose a linguistically-motivated query expansionframework that recognizes and en-codes significant query constituents thatcharacterize query intent in order to improve retrieval performance.Concepts-of-Interest are recognized as the core concepts that represent thegist of the search goal whilst the remaining query constituents which serve tospecify the search goal and complete the query structure are classified asdescriptive, relational or structural. Acknowledging the need to formsemantically-associated base pairs for the purpose of extracting relatedpotential expansion concepts, an algorithm which capitalizes on syntacticaldependencies to capture relationships between adjacent and non-adjacent queryconcepts is proposed. Lastly, a robust weighting scheme that duly emphasizesthe importance of query constituents based on their linguistic role within theexpanded query is presented. We demonstrate improvements in retrievaleffectiveness in terms of increased mean average precision (MAP) garnered bythe proposed linguistic-based query expansion framework through experimentationon the TREC ad hoc test collections.

A Linguistically Driven Framework for Query Expansion via Grammatical Constituent Highlighting and Role-Based Concept Weighting