A Convolutional Neural Network for Modelling Sentences

Understand

The ability to accurately represent sentences is central to language understanding.

• We describe a convolutional architecture dubbed the Dynamic Convolutional Neural Network (DCNN) that we adopt for the semantic modelling of sentences.
• The network uses Dynamic k-Max Pooling, a global pooling operation over linear sequences.
• The network handles input sentences of varying length and induces a feature graph over the sentence that is capable of explicitly capturing short and long-range relations.