Name
Abstract | ||
|---|---|---|
In this paper, we propose a graph-based translation model which takes advantage of discontinuous phrases. The model segments a graph which combines bigram and dependency relations into subgraphs and produces translations by combining translations of these subgraphs. Experiments on Chinese‐English and German‐English tasks show that our system is significantly better than the phrase-based model. By explicitly modeling the graph segmentation, our system gains further improvement. |
Year | Venue | Field |
|---|---|---|
2016 | SedMT@NAACL-HLT | Comparability graph,Computer science,Phrase,Theoretical computer science,Artificial intelligence,Natural language processing,Dependency graph,Voltage graph,Null graph,Graph product,Clique-width,Machine learning,Complement graph |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liangyou Li | 1 | 2 | 2.72 |
| Andy Way | 2 | 881 | 126.78 |
| Qun Liu | 3 | 2149 | 203.11 |