TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)
December 30, 2022 ยท Declared Dead ยท ๐ AAAI Conference on Artificial Intelligence
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Authors
Rฤzvan-Alexandru Smฤdu, George-Eduard Zaharia, Andrei-Marius Avram, Dumitru-Clementin Cercel, Mihai Dascalu, Florin Pop
arXiv ID
2301.06902
Category
cs.CL: Computation & Language
Citations
1
Venue
AAAI Conference on Artificial Intelligence
Last Checked
5 months ago
Abstract
Keyphrase identification and classification is a Natural Language Processing and Information Retrieval task that involves extracting relevant groups of words from a given text related to the main topic. In this work, we focus on extracting keyphrases from scientific documents. We introduce TA-DA, a Topic-Aware Domain Adaptation framework for keyphrase extraction that integrates Multi-Task Learning with Adversarial Training and Domain Adaptation. Our approach improves performance over baseline models by up to 5% in the exact match of the F1-score.
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