WUT at SemEval-2019 Task 9: Domain-Adversarial Neural Networks for Domain Adaptation in Suggestion Mining
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Summary
The submitted solution for this text classification problem explores the idea of treating different suggestions’ sources as one of the settings of Transfer Learning - Domain Adaptation.
- Type
- article
- Published
- 2019-06-01
- Cited by
- 3
- References
- 16
- Access
- Open access
- OpenAlex
- https://openalex.org/W2955455867
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:184482768
Keywords
SemEval, Computer science, Domain (mathematical analysis), Adversarial system, Domain adaptation
References
- A theoretical review of the speech act of suggesting: towards a taxonomy for its use in FLT
- A Review Corpus for Argumentation Analysis
- Visualizing Data using t-SNE
- Towards the Extraction of Customer-to-Customer Suggestions from Reviews
- Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
- Bag of Tricks for Efficient Text Classification
- Part-of-Speech Tagging for Twitter with Adversarial Neural Networks
- Domain-Adversarial Training of Neural Networks
- Deep Contextualized Word Representations
- SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums
- Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Second Edition
- Web data mining: exploring hyperlinks, contents, and usage data
- Unsupervised Domain Adaptation by Backpropagation
- A Structured Self-attentive Sentence Embedding
Cited by
- SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums
- An adversarial discriminative temporal convolutional network for EEG-based cross-domain emotion recognition
- Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification
- Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification