Multichannel Convolutional Neural Network for Biological Relation Extraction

Figure 2

The architecture of the proposed MCCNN. In this example, the length of input sentence is 10, the input word embedding dimension is 5, and there are 5-word embedding channels. Therefore, the size of multichannel inputs is . Two windows sizes 3 and 4 are used in this example. The green part is generate by (1). The orange part, representing the max-pooling result, is generated by take the maximum value of the blue part through (3). Since there are 2 filters for each window size, 2 features are produced. These extracted features are then concatenated together and fed to a Softmax layer for classification.