DOI: 10.1109/iccas.2013.6704146
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Abstract: Question answering generally generates the answer to the question by extracting the named entity from the sentences containing the answer to the question from information sources. However, it is not always true that a named entity is an answer to the question. So we propose a method for generating the answer sentence using statistical machine translation. The probability models are constructed by learning from enormous samples of the set of question sentence, extracted sentence, and answer sentence. The quest…

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