Abstract
Our ongoing project is aimed at improving information access to narrow-domain collections of questions and answers. This poster demonstrates how out-of-the-box tools and domain dictionaries can be applied to community question answering (CQA) content in health domain. This approach can be used to improve user interfaces and search over CQA data, as well as to evaluate content quality. The study is a first-time use of a sizable dataset from the Russian CQA site Otvety@Mail.Ru.
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Beloborodov, A., Kuznetsov, A., Braslavski, P. (2013). Characterizing Health-Related Community Question Answering. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_59
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DOI: https://doi.org/10.1007/978-3-642-36973-5_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36972-8
Online ISBN: 978-3-642-36973-5
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