Dependency-based Convolutional Neural Networks for Sentence Embedding
2015-07-07IJCNLP 2015Code Available0· sign in to hype
Mingbo Ma, Liang Huang, Bing Xiang, Bo-Wen Zhou
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Abstract
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.