← Back to papers
2019 SEMEVAL SemEval 2019

MIDAS at SemEval-2019 Task 9: Suggestion Mining from Online Reviews using ULMFit

🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🐣 Hot Topic Early Bird — language model fine-tuning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Sarthak Anand , Debanjan Mahata , Kartik Aggarwal , Laiba Mehnaz , Simra Shahid , Haimin Zhang , Yaman Kumar , Rajiv Shah , Karan Uppal

Topics

Natural Language Processing > Applications > Text Classification Natural Language Processing > Resources & Methods > Large Language Models Machine Learning > Learning Types > Transfer Learning

Keywords

text classification language model fine-tuning online review suggestion mining
Download PDF

Related papers

CAMsterdam at SemEval-2019 Task 6: Neural and graph-based feature extraction for the identification of offensive tweets 2019
JU_ETCE_17_21 at SemEval-2019 Task 6: Efficient Machine Learning and Neural Network Approaches for Identifying and Categorizing Offensive Language in Tweets 2019
Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification 2019
Lijunyi at SemEval-2019 Task 9: An attention-based LSTM and ensemble of different models for suggestion mining from online reviews and forums 2019
CX-ST-RNM at SemEval-2019 Task 3: Fusion of Recurrent Neural Networks Based on Contextualized and Static Word Representations for Contextual Emotion Detection 2019