Name
Abstract | ||
|---|---|---|
We address the problem of large-scale automatic detection of online reviews without using any human labels. We propose an efficient method that combines two basic ideas: Building a classifier from a large number of noisy examples and using the structure of the website to enhance the performance of this classifier. Experiments suggest that our method is competitive against supervised learning methods that mandate expensive human effort. |
Year | Venue | Keywords |
|---|---|---|
2009 | HLT-NAACL | basic idea,sans human label,noisy example,large-scale automatic detection,supervised learning method,large number,human label,efficient method,online review,mandate expensive human effort,review page,supervised learning |
DocType | Citations | PageRank |
Conference | 4 | 0.45 |
References | Authors | |
18 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luciano Barbosa | 1 | 714 | 43.86 |
| Ravi Kumar | 2 | 13932 | 1642.48 |
| Bo Pang | 3 | 5795 | 451.00 |
| Andrew Tomkins | 4 | 9388 | 1401.23 |