Exploiting Position and Contextual Word Embeddings for Keyphrase Extraction from Scientific Papers
Krutarth Patel, Cornelia Caragea · 2021
Keyphrases associated with research papers provide an effective way to find useful information in the large and growing scholarly digital collections.In this paper, we present KPRank, an unsupervised graph-based algorithm for keyphrase extraction that exploits both positional information and contextual word embeddings into a biased PageRank.Our experimental results on five benchmark datasets show that KPRank that uses contextual word embeddings with additional position signal outperforms previous approaches and strong baselines for this task.