Bo Zhang1, Haowen Wang1, #, Longquan Jiang1, Shuhan Yuan2, Meizi Li1, *
CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1273-1288, 2020, DOI:10.32604/cmc.2020.07269
Abstract Deep learning models have been shown to have great advantages in answer
selection tasks. The existing models, which employ encoder-decoder recurrent neural
network (RNN), have been demonstrated to be effective. However, the traditional
RNN-based models still suffer from limitations such as 1) high-dimensional data
representation in natural language processing and 2) biased attentive weights for
subsequent words in traditional time series models. In this study, a new answer selection
model is proposed based on the Bidirectional Long Short-Term Memory (Bi-LSTM) and
attention mechanism. The proposed model is able to generate the more effective
question-answer pair representation. Experiments on a question… More >
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