Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank, Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Chris Manning, Andrew Ng and Chris Potts. Conference on Empirical Methods in Natural Language Processing (EMNLP 2013, Oral). pdf;Website with Live Demo and Downloads
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank by Socher et al. introduces Recursive Neural Tensor Network (RNTN), a model for extracting sentiment from longer phrases that outperforms previous models. The model is trained on a corpus of 215,154 phrases that were labelled using Amazon Turk. Using RNTN, single sentence accuracy increases from 80% up to 85.4%; and negation is accurately captured (a task no previous model succeeded at).