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A Convolutional Neural Network for Modelling Sentences

Abstract:

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, capable of explicitly capturing short and long-range relations. The net...

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Journal:
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics More from this journal
Publication date:
2014-06-01
UUID:
uuid:6f1ee516-1e8c-4d0f-b238-2e5c655b7110
Local pid:
cs:8536
Deposit date:
2015-03-31

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