Unsupervised Keyphrase Extraction with Multipartite Graphs
Florian Boudin · 2018
We propose an unsupervised keyphrase extraction model that encodes topical information within a multipartite graph structure.Our model represents keyphrase candidates and topics in a single graph and exploits their mutually reinforcing relationship to improve candidate ranking.We further introduce a novel mechanism to incorporate keyphrase selection preferences into the model.Experiments conducted on three widely used datasets show significant improvements over state-of-the-art graph-based models.