Papers with sentence classification task
A Deep Neural Network Sentence Level Classification Method with Context Information (D18-1)
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| Challenge: | Existing methods that use context for sentence classification are difficult to scale . Usually, sentences are treated as separate instances for the task . however, in many situations the sentence that is the focus of classification appears in a context that can provide additional information. |
| Approach: | They propose a method that uses potentially large contexts to classify sentences . they use an LSTM, and short-span features to classize sentences based on a stacked CNN . |
| Outcome: | The proposed method consistently improves on two different datasets. |
Modularized Syntactic Neural Networks for Sentence Classification (2020.emnlp-main)
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| Challenge: | Existing models for sentence classification use local information of sub-trees, but new models use global context . |
| Approach: | They propose a tree-parallel mini-batch strategy for efficient training and predicting sentences . they propose to use syntax category labels to model sub-trees . |
| Outcome: | The proposed model outperforms state-of-the-art tree-based methods on the sentence classification task. |
Design and Evaluation of SentiEcon: a fine-grained Economic/Financial Sentiment Lexicon from a Corpus of Business News (2020.lrec-1)
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| Challenge: | SentiEcon is a large, comprehensive, domain-specific computational lexicon designed for sentiment analysis applications. |
| Approach: | They describe a large, comprehensive, domain-specific computational lexicon designed for sentiment analysis applications. |
| Outcome: | The proposed lexicon significantly improves when adding sentiment words to the general-language sentiment lexiconic. |