Citation-Enhanced Keyphrase Extraction from Research Papers: A Supervised Approach
Authors
Cornelia Caragea, Florin Bulgarov, Andreea Godea, and Sujatha Das Gollapalli
Abstract
Given the large amounts of online textual documents available these days, e.g., news articles, weblogs, and scientific papers, effective methods for extracting keyphrases, which provide a high-level topic description of a document, are greatly needed. In this paper, we propose a supervised model for keyphrase extraction from research papers, which are embedded in citation networks. To this end, we design novel features based on citation network information and use them in conjunction with traditional features for keyphrase extraction to obtain remarkable improvements in performance over strong baselines.
Keywords:
Keyphrase extraction, citation contexts, citing contexts, cited contexts, citation networks, supervised approach to keyphrase extraction
Reference:
Cornelia Caragea, Florin Bulgarov, Andreea Godea, and Sujatha Das Gollapalli. "Citation-Enhanced Keyphrase Extraction from Research Papers: A Supervised Approach." In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), Doha, Qatar, 2014. [pdf] [poster] [code] [data] [project website]