Papers by Pavithra Rajendran
Sentiment-Stance-Specificity (SSS) Dataset: Identifying Support-based Entailment among Opinions. (L18-1)
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| Challenge: | Argument mining is a method for extracting argument components and structures from natural language texts. |
| Approach: | They propose to model arguments as a set of premises that either support each other or collectively support a conclusion. |
| Outcome: | The proposed rules give an overall accuracy of 0.83 for the three datasets. |
Is Something Better than Nothing? Automatically Predicting Stance-based Arguments Using Deep Learning and Small Labelled Dataset (N18-2)
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| Challenge: | Argument mining is a subset of NLP that deals with extracting arguments from user-based content. |
| Approach: | They propose to use weakly supervised and semi-supervised methods to automatically annotate reviews and provide large annotated datasets. |
| Outcome: | The proposed methods can be used to learn better models for implicit/explicit opinion classification. |