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ACL
2006
13 years 11 months ago
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
FLAIRS
2004
13 years 11 months ago
Semi-Supervised Sequence Classification with HMMs
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Shi Zhong
ICPR
2006
IEEE
14 years 11 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
SIGMOD
2004
ACM
150views Database» more  SIGMOD 2004»
14 years 10 months ago
When one Sample is not Enough: Improving Text Database Selection Using Shrinkage
Database selection is an important step when searching over large numbers of distributed text databases. The database selection task relies on statistical summaries of the databas...
Panagiotis G. Ipeirotis, Luis Gravano
SIGIR
2010
ACM
13 years 10 months ago
SED: supervised experimental design and its application to text classification
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...
Yi Zhen, Dit-Yan Yeung