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- W2579367166 abstract "We present in this paper a purely rule-based system for Question Classification which we divide into two parts: The first is the extraction of relevant words from a question by use of its structure, and the second is the classification of questions based on rules that associate these words to Concepts. We achieve an accuracy of 97.2%, close to a 6 point improvement over the previous State of the Art of 91.6%. Additionally, we believe that machine learning algorithms can be applied on top of this method to further improve accuracy." @default.
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- W2579367166 date "2016-12-16" @default.
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- W2579367166 title "High Accuracy Rule-based Question Classification using Question Syntax and Semantics" @default.
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