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

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.