Name
Abstract | ||
|---|---|---|
We propose an event-driven model for headline generation. Given an input document, the system identifies a key event chain by extracting a set of structural events that describe them. Then a novel multi-sentence compression algorithm is used to fuse the extracted events, generating a headline for the document. Our model can be viewed as a novel combination of extractive and abstractive headline generation, combining the advantages of both methods using event structures. Standard evaluation shows that our model achieves the best performance compared with previous state-of-the-art systems. |
Year | Venue | Field |
|---|---|---|
2015 | PROCEEDINGS OF THE 53RD ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 7TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 1 | Headline,Computer science,Sentence compression,Speech recognition,Artificial intelligence,Natural language processing,Data compression,Fuse (electrical) |
DocType | Volume | Citations |
Conference | P15-1 | 2 |
PageRank | References | Authors |
0.39 | 22 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Sun | 1 | 2 | 0.73 |
| Yue Zhang | 2 | 1364 | 114.17 |
| Meishan Zhang | 3 | 221 | 20.36 |
| Donghong Ji | 4 | 892 | 120.08 |