Fig. 2.

Three primary deep learning models to capture sentence similarity. The first is the Convolutional Neural Network Model (1.1 and 1.2), which applies image-related convolutional processing to text. The second is LSTM or Recurrent Neural Network (2 in the figure), which aims to learn the semantics aligned with the input sequence. The third is Encoder-Decoder network (3 in the figure), where the encoder aims to compress the semantics of a sentence into a vector and decoder aims to re-generate the original sentence from the vector. FC layers: fully-connected layers. All three models use fully-connected layers as final stages