Computer Science ›› 2016, Vol. 43 ›› Issue (12): 115-119.doi: 10.11896/j.issn.1002-137X.2016.12.020

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Research on Problem Classification Method Based on Deep Learning

LI Chao, CHAI Yu-mei, NAN Xiao-fei and GAO Ming-lei   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Question classification is an important part of question answering system.But question classification requires the strategy of extracting features and the continuous optimization of characteristic rules at the present stage.The methodof deep learning is feasible in the question classification by the way of self learning question characteristics to represent and understand the problem so as to avoid formulating artificial features and reduce labor costs.For question classification,the long-short term memory(LSTM) model and the convolution neural network (CNN) model were improved,combining the advantages of these two models into a new learning framework (LSTM-MFCNN) to strengthen the semantic study of word order and study of depth characteristics.Experimental results show that the proposed method still has good performance under the condition of no need to formulate the characteristic rules,and the accuracy of this me-thod is 93.08%.

Key words: Question classification,Deep learning,CNN,LSTM,Machine learning

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