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Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
A Sentiment Treebank that includes fine grained sentiment labels for 215,154 phrases in the parse trees of 11,855 sentences and presents new challenges for sentiment compositionality, and introduces the Recursive Neural Tensor Network.
Optimal Feature Extraction based Machine Learning Approach for Sarcasm Type Detection in News Headlines
Data pre-processing makes the data clean so that the performance of the classifier will be enhance, and result shows the improve performance in sarcasm detection using the optimal feature sets.
Semantic Compositionality and Deep Learning for Sentiment Analysis
This paper creates baselines to take advantage of the new depth of information available in the new dataset, which outperform previous baselines on classical tasks and achieve near state-of-the-art performance on positive/negative classification.
Detecting Audio / Video Asynchrony
This project will attempt to detect A/V misalignment in standard (nonstreaming) movie clips by comparing the progression of these audio and video features over a segment of the movie clip.