Simple similarity-based question answering strategies for biomedical text

David Martinez*, Andrew MacKinlay, Diego Molla-Aliod, Lawrence Cavedon, Karin Verspoor

*Corresponding author for this work

Research output: Contribution to journalConference paper

2 Citations (Scopus)

Abstract

We introduce an approach to question answering in the biomedical domain that utilises similarity matching of question/answer pairs in a document, or a set of background documents, to select the best answer to a multiple-choice question. We explored a range of possible similarity matching methods, ranging from simple word overlap, to dependency graph matching, to feature-based vector similarity models that incorporate lexical, syntactic and/or semantic features. We found that while these methods performed reasonably well on a small training set, they did not generalise well to the final test data.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalCEUR Workshop Proceedings
Volume1178
Publication statusPublished - 2012

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  • Cite this

    Martinez, D., MacKinlay, A., Molla-Aliod, D., Cavedon, L., & Verspoor, K. (2012). Simple similarity-based question answering strategies for biomedical text. CEUR Workshop Proceedings, 1178, 1-13.