Abstract
Question analysis is an important component of a general Question Answering (QA) system. Question analysis has different angles and functions. The paper focuses on recognition of question subject in QA system. The goal of subject recognition is to identify given question according to special domain. We discuss three approaches to identify subjects of questions, then quantificationally evaluate effect of machine learning methods by a series of experiments. The results show that Naive Bayes gains the best accuracy and efficiency than other learning methods and two ways of feature extraction proposed by the paper improve accuracy for most of learning methods.
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© 2016 Springer Science+Business Media Singapore
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Huo, Lf., Zhang, Lm., Zhao, Xq. (2016). Question Recognition Based on Subject. In: Hung, J., Yen, N., Li, KC. (eds) Frontier Computing. Lecture Notes in Electrical Engineering, vol 375. Springer, Singapore. https://doi.org/10.1007/978-981-10-0539-8_35
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DOI: https://doi.org/10.1007/978-981-10-0539-8_35
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