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ICML
2010
IEEE
15 years 3 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
128
Voted
EMNLP
2009
15 years 6 days ago
Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation class...
Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zh...
EMNLP
2010
15 years 12 days ago
A Semi-Supervised Method to Learn and Construct Taxonomies Using the Web
Although many algorithms have been developed to harvest lexical resources, few organize the mined terms into taxonomies. We propose (1) a semi-supervised algorithm that uses a roo...
Zornitsa Kozareva, Eduard H. Hovy
COLING
2010
14 years 9 months ago
Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints
In opinion mining of product reviews, one often wants to produce a summary of opinions based on product features/attributes. However, for the same feature, people can express it w...
Zhongwu Zhai, Bing Liu, Hua Xu, Peifa Jia
CORR
2012
Springer
228views Education» more  CORR 2012»
13 years 10 months ago
Active Semi-Supervised Learning using Submodular Functions
Andrew Guillory, Jeff A. Bilmes