  This paper challenges a cross-genre document retrieval task, where the
queries are in formal writing and the target documents are in conversational
writing. In this task, a query, is a sentence extracted from either a summary
or a plot of an episode in a TV show, and the target document consists of
transcripts from the corresponding episode. To establish a strong baseline, we
employ the current state-of-the-art search engine to perform document retrieval
on the dataset collected for this work. We then introduce a structure reranking
approach to improve the initial ranking by utilizing syntactic and semantic
structures generated by NLP tools. Our evaluation shows an improvement of more
than 4% when the structure reranking is applied, which is very promising.
