2020
AACL
AACL 2020
Intent Segmentation of User Queries Via Discourse Parsing
Abstract
AbstractIn this paper, we explore a new approach based on discourse analysis for the task of intent segmentation. Our target texts are user queries from a real-world chatbot. Our results show the feasibility of our approach with an F1-score of 82.97 points, and some advantages and disadvantages compared to two machine learning baselines: BERT and LSTM+CRF.
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Conference Pioneer
— AACL 2020
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Interdisciplinary Bridge
— Artificial Intelligence and Interdisciplinary and Natural Language Processing
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Keyword Pioneer
— intent segmentation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing, Reinforcement Learning, Speech & Audio