Name
Abstract | ||
|---|---|---|
Keyphrase is an efficient representation of the main idea of documents. While background knowledge can provide valuable information about documents, they are rarely incorporated in keyphrase extraction methods. In this paper, we propose WikiRank, an unsupervised method for keyphrase extraction based on the background knowledge from Wikipedia. Firstly, we construct a semantic graph for the document. Then we transform the keyphrase extraction problem into an optimization problem on the graph. Finally, we get the optimal keyphrase set to be the output. Our method obtains improvements over other state-of-art models by more than 2% in F1-score. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computation and Language | Graph,Computer science,Artificial intelligence,Natural language processing,Optimization problem |
DocType | Volume | Citations |
Journal | abs/1803.09000 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Yu | 1 | 24 | 13.21 |
| Vincent Ng | 2 | 1 | 3.73 |