13 search results - page 1 / 3 » Combining Labeled and Unlabeled Data for Learning Cross-Docu... |
102
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IJCNLP
2004
Springer
15 years 5 months ago
2004
Springer
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
116
Voted
EMNLP
2007
15 years 1 months ago
2007
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
120
Voted
CIKM
2011
Springer
14 years 10 days ago
2011
Springer
Extracting information from web pages is an important problem; it has several applications such as providing improved search results and construction of databases to serve user qu...
116
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ICML
2005
IEEE
16 years 1 months ago
2005
IEEE
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
99
Voted
ICCV
2009
IEEE
16 years 4 months ago
2009
IEEE
Graph-based semi-supervised learning has gained considerable
interests in the past several years thanks to its effectiveness
in combining labeled and unlabeled data through
labe...