Name
Abstract | ||
|---|---|---|
Previous work in referring expression generation has explored general purpose techniques for attribute selection and surface realization. However, most of this work did not take into account: a) stylistic differences between speakers; or b) trainable surface realization approaches that combine semantic and word order information. In this paper we describe and evaluate several end-to-end referring expression generation algorithms that take into consideration speaker style and use data-driven surface realization techniques. |
Year | Venue | Keywords |
|---|---|---|
2008 | CoNLL | previous work,data-driven surface realization technique,stylistic difference,general purpose technique,attribute selection,surface realization,consideration speaker style,expression generation,trainable surface realization approach,expression generation algorithm |
Field | DocType | Citations |
Referring expression generation,Word order,Feature selection,General purpose,Computer science,Speech recognition,Artificial intelligence,Natural language processing | Conference | 10 |
PageRank | References | Authors |
0.63 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giuseppe Di Fabbrizio | 1 | 330 | 44.45 |
| Amanda J. Stent | 2 | 1094 | 103.35 |
| Srinivas Bangalore | 3 | 1319 | 157.37 |