Abstract
In this paper, we discuss our novel, open-domain question answering (Q/A) system, R/quest. We use web page snippets from GoogleTM to extract short paragraphs that become candidate answers. We performed an evaluation that showed, on average, 1.4 times higher recall and a slightly higher precision by using a question expansion method. We have modified the Cosine Coefficient Similarity Measure to take into account the rank position of a candidate answer and its length. This produces an effective ranking scheme. We have a new question refinement method that improves recall. We further enhanced performance by adding a Boolean NOT operator. R/quest on average provides an answer within the top 2 to 3 paragraphs shown to the user. We consider this to be a considerable advance over search engines that provide millions of ranked web pages which must be searched manually to find the information needed.
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Morrissey, J., Zhao, R. (2013). R/quest: A Question Answering System. In: Larsen, H.L., Martin-Bautista, M.J., Vila, M.A., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2013. Lecture Notes in Computer Science(), vol 8132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40769-7_7
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DOI: https://doi.org/10.1007/978-3-642-40769-7_7
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