Name
Abstract | ||
|---|---|---|
We present a preliminary study on unsu-pervised preposition sense disambiguation (PSD), comparing different models and training techniques (EM, MAP-EM with L0 norm, Bayesian inference using Gibbs sampling). To our knowledge, this is the first attempt at un-supervised preposition sense disambiguation. Our best accuracy reaches 56%, a significant improvement (at p |
Year | Venue | Keywords |
|---|---|---|
2011 | ACL (Short Papers) | training technique,unsupervised preposition sense disambiguation,bayesian inference,different model,l0 norm,gibbs sampling,un-supervised preposition sense disambiguation,best accuracy,unsu-pervised preposition sense disambiguation,significant improvement,preliminary study |
Field | DocType | Volume |
Bayesian inference,Computer science,Natural language processing,Artificial intelligence,Gibbs sampling,Machine learning | Conference | P11-2 |
Citations | PageRank | References |
4 | 0.41 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dirk Hovy | 1 | 490 | 40.44 |
| Ashish Vaswani | 2 | 901 | 32.81 |
| Stephen Tratz | 3 | 195 | 15.29 |
| David Chiang | 4 | 2843 | 144.76 |
| Eduard H. Hovy | 5 | 7450 | 663.27 |