Name
Title | ||
|---|---|---|
Weakly Supervised Slot Tagging with Partially Labeled Sequences from Web Search Click Logs. |
Abstract | ||
|---|---|---|
In this paper, we apply a weakly-supervised learning approach for slot tagging using conditional random fields by exploiting web search click logs. We extend the constrained lattice training of T¨¨ om et al. (2013) to non-linear conditional random fields in which latent variables mediate between observations and labels. When combined with a novel initialization scheme that leverages unlabeled data, we show that our method gives significant improvement over strong supervised and weakly-supervised baselines. |
Year | Venue | Field |
|---|---|---|
2015 | HLT-NAACL | Conditional random field,Data mining,Computer science,Latent variable,Artificial intelligence,Initialization,Machine learning |
DocType | Citations | PageRank |
Conference | 15 | 0.66 |
References | Authors | |
18 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Young-Bum Kim | 1 | 112 | 13.60 |
| Minwoo Jeong | 2 | 42 | 2.49 |
| Karl Stratos | 3 | 328 | 21.07 |
| Ruhi Sarikaya | 4 | 698 | 64.49 |