Recently, deep neural networks (DNNs) have been effectively used to learn robust syntactic and semantic representations behind complex structures.
we propose a novel DNN framework which combines Long Short-Term Memory (LSTM) (Hochreiter and Schmidhuber, 1997) and Convolutional Neural Networks (CNN) (LeCun et al., 1989) with a multi-attention layer.