2013 RecursiveDeepModelsforSemanticC

• (Socher et al., 2013) ⇒ Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, and Christopher Potts. (2013). “Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank.” In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013).

Subject Headings: Semantic Compositionality (SC) Principle; Semantic Compositionality (SC) Task.

Cited By

• http://scholar.google.com/scholar?q=%222013%22+Recursive+Deep+Models+for+Semantic+Compositionality+Over+a+Sentiment+Treebank

Quotes

Abstract

Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. Further progress towards understanding compositionality in tasks such as sentiment detection requires richer supervised training and evaluation resources and more powerful models of composition. To remedy this, we introduce a Sentiment Treebank. It includes fine grained sentiment labels for 215, 154 phrases in the parse trees of 11, 855 sentences and presents new challenges for sentiment compositionality. To address them, we introduce the Recursive Neural Tensor Network. When trained on the new treebank, this model outperforms all previous methods on several metrics. It pushes the state of the art in single sentence positive / negative classification from 80% up to 85.4%. The accuracy of predicting fine-grained sentiment labels for all phrases reaches 80.7%, an improvement of 9.7% over bag of features baselines. Lastly, it is the only model that can accurately capture the effects of negation and its scope at various tree levels for both positive and negative phrases.

BibTeX

@inproceedings{2013_RecursiveDeepModelsforSemanticC,
  author    = {Richard Socher and
               Alex Perelygin and
               Jean Wu and
               Jason Chuang and
               Christopher D. Manning and
               Andrew Y. Ng and
               [[Christopher Potts]]},
  title     = {Recursive Deep Models for Semantic Compositionality Over a Sentiment
               Treebank},
  booktitle = {Proceedings of the 2013 Conference on Empirical Methods in Natural
               Language Processing (EMNLP 2013)},
  pages     = {1631--1642},
  publisher = {ACL},
  year      = {2013},
  url       = {https://www.aclweb.org/anthology/D13-1170/},
}

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 RecursiveDeepModelsforSemanticC	Christopher D. Manning Andrew Y. Ng Christopher Potts Richard Socher Alex Perelygin Jean Wu Jason Chuang			Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank						2013