In Information Retrieval (IR) in general and Question Answering (QA) in particular, queries and relevant textual content often significantly differ in their properties and are therefore difficult to relate with traditional IR methods, . key-word matching. In this paper we describe an algorithm that addresses this problem, but rather than looking at it on a term matching/term reformulation level, we focus on the syntactic differences between questions and relevant text passages. To this end we propose a novel algorithm that analyzes dependency structures of queries and known relevant text passages and acquires transformational patterns that can be used to.
