WUT at SemEval-2019 task 9: Domain-adversarial neural networks for domain adaptation in suggestion mining

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Abstract

We present a system for cross-domain suggestion mining, prepared for the SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums (Subtask B). Our 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. Our experiments show that without any labeled target domain examples during training time, we are capable of proposing a system, reaching up to 0.778 in terms of F1 score on test dataset, based on Target Preserving Domain-Adversarial Neural Networks.

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APA

Klimaszewski, M., & Andruszkiewicz, P. (2019). WUT at SemEval-2019 task 9: Domain-adversarial neural networks for domain adaptation in suggestion mining. In NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop (pp. 1262–1266). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s19-2221

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