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NAACL
2004
13 years 9 months ago
Name Tagging with Word Clusters and Discriminative Training
We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is...
Scott Miller, Jethran Guinness, Alex Zamanian
ACL
2004
13 years 9 months ago
Chinese Verb Sense Discrimination Using an EM Clustering Model with Rich Linguistic Features
This paper discusses the application of the Expectation-Maximization (EM) clustering algorithm to the task of Chinese verb sense discrimination. The model utilized rich linguistic...
Jinying Chen, Martha Stone Palmer
ICCV
2005
IEEE
14 years 9 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
CICLING
2005
Springer
14 years 1 months ago
Name Discrimination by Clustering Similar Contexts
It is relatively common for different people or organizations to share the same name. Given the increasing amount of information available online, this results in the ever growing...
Ted Pedersen, Amruta Purandare, Anagha Kulkarni
AAAI
2006
13 years 9 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...