Name
Abstract | ||
|---|---|---|
This paper studies keyphrase extraction in real-world scenarios where documents are from diverse domains and have variant content quality. We curate and release OpenKP, a large scale open domain keyphrase extraction dataset with near one hundred thousand web documents and expert keyphrase annotations. To handle the variations of domain and content quality, we develop BLING-KPE, a neural keyphrase extraction model that goes beyond language understanding using visual presentations of documents and weak supervision from search queries. Experimental results on OpenKP confirm the effectiveness of BLING-KPE and the contributions of its neural architecture, visual features, and search log weak supervision. Zero-shot evaluations on DUC-2001 demonstrate the improved generalization ability of learning from the open domain data compared to a specific domain. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.18653/v1/D19-1521 | EMNLP/IJCNLP (1) |
DocType | Volume | ISSN |
Conference | D19-1 | EMNLP-IJCNLP 2019 |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lee Xiong | 1 | 2 | 0.37 |
| Chuan Hu | 2 | 9 | 2.54 |
| Chen-Yan Xiong | 3 | 405 | 30.82 |
| daniel filipe barros campos | 4 | 28 | 8.61 |
| Arnold Overwijk | 5 | 2 | 0.71 |
| Xiayu Huang | 6 | 2 | 0.37 |