Using discourse analysis for the design of information retrieval interaction mechanisms
SIGIR '83 Proceedings of the 6th annual international ACM SIGIR conference on Research and development in information retrieval
The TREC robust retrieval track
ACM SIGIR Forum
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
A retrospective study of probabilistic context-based retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Anaphora and Discourse Structure
Computational Linguistics
Rhetorical relations for information retrieval
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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In ad hoc information retrieval (IR), some information need (e.g., find the advantages and disadvantages of smoking) requires the explicit identification of information related to the discourse type (e.g., advantages/ disadvantages) as well as to the topic (e.g., smoking). Such information need is not uncommon and may not be satisfied by using conventional retrieval methods. We extend existing retrieval models by adding a re-ranking strategy based on a novel graph-based retrieval model using document contexts that are called information units (IU). For evaluation, we focused on a discourse type that appeared in a subset of TREC topics where the retrieval effectiveness achieved by our conventional retrieval models for those topics was low. We showed that our approach is able to enhance the retrieval effectiveness for the selected TREC topics. This shows that our preliminary investigation is promising and deserves further investigation.