Paper: Citation-Enhanced Keyphrase Extraction from Research Papers: A Supervised Approach

ACL ID D14-1150
Title Citation-Enhanced Keyphrase Extraction from Research Papers: A Supervised Approach
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Given the large amounts of online textual documents available these days, e.g., news articles, weblogs, and scientific papers, ef- fective methods for extracting keyphrases, which provide a high-level topic descrip- tion of a document, are greatly needed. In this paper, we propose a supervised model for keyphrase extraction from research pa- pers, which are embedded in citation net- works. To this end, we design novel fea- tures based on citation network informa- tion and use them in conjunction with tra- ditional features for keyphrase extraction to obtain remarkable improvements in per- formance over strong baselines.