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.
@article{arxiv.2301.06902,
title = {TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)},
author = {Răzvan-Alexandru Smădu and George-Eduard Zaharia and Andrei-Marius Avram and Dumitru-Clementin Cercel and Mihai Dascalu and Florin Pop},
journal= {arXiv preprint arXiv:2301.06902},
year = {2023}
}