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IJCNLP
2004
Springer
15 years 6 months ago
Combining Labeled and Unlabeled Data for Learning Cross-Document Structural Relationships
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...
Zhu Zhang, Dragomir R. Radev
93
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CIKM
2003
Springer
15 years 6 months ago
Learning cross-document structural relationships using boosting
Zhu Zhang, Jahna Otterbacher, Dragomir R. Radev
183
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SIGMOD
2005
ACM
155views Database» more  SIGMOD 2005»
16 years 1 months ago
On Boosting Holism in XML Twig Pattern Matching using Structural Indexing Techniques
Searching for all occurrences of a twig pattern in an XML document is an important operation in XML query processing. Recently a holistic method TwigStack [2] has been proposed. T...
Ting Chen, Jiaheng Lu, Tok Wang Ling
144
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ETVC
2008
15 years 2 months ago
Intrinsic Geometries in Learning
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
Richard Nock, Frank Nielsen
ICPR
2002
IEEE
16 years 2 months ago
Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker Detection
Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovi...