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COLING
2008
13 years 10 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li
EMNLP
2010
13 years 6 months ago
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Amarnag Subramanya, Slav Petrov, Fernando Pereira
ACL
2008
13 years 10 months ago
Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields
This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accompli...
Gideon S. Mann, Andrew McCallum
NIPS
2004
13 years 10 months ago
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...
ICDM
2005
IEEE
217views Data Mining» more  ICDM 2005»
14 years 2 months ago
Improving Automatic Query Classification via Semi-Supervised Learning
Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. Such classification becomes critical if th...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...