Dependency-based Convolutional Neural Networks for Sentence Embedding

Understand

In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies.

• To exploit both deep learning and linguistic structures, we propose a tree-based convolutional neural network model which exploit various long-distance relationships between words.
• Our model improves the sequential baselines on all three sentiment and question classification tasks, and achieves the highest published accuracy on TREC.