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92
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SKG
2006
IEEE
15 years 5 months ago
Embedding the Semantic Knowledge in Convolution Kernels
Convolution kernels, such as tree kernel and subsequence kernel are useful for natural language processing tasks. However, most of them ignore the semantic knowledge. In order to ...
Kebin Liu, Fang Li, Ying Han, Lei Liu
102
Voted
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
14 years 10 months ago
Large-Scale Support Vector Learning with Structural Kernels
Abstract. In this paper, we present an extensive study of the cuttingplane algorithm (CPA) applied to structural kernels for advanced text classification on large datasets. In par...
Aliaksei Severyn, Alessandro Moschitti
98
Voted
CCR
1998
96views more  CCR 1998»
14 years 11 months ago
On routes and multicast trees in the Internet
: Multicasting has an increasing importance for network applications such as groupware or videoconferencing. Several multicast routing protocols have been defined. However they can...
Jean-Jacques Pansiot, Dominique Grad
TCAD
2002
128views more  TCAD 2002»
14 years 11 months ago
Preferred direction Steiner trees
Interconnect optimization for VLSI circuits has received wide attention. To model routing surfaces, multiple circuit layers are freabstracted as a single rectilinear plane, ignori...
Mehmet Can Yildiz, Patrick H. Madden
ACL
2004
15 years 1 months ago
Convolution Kernels with Feature Selection for Natural Language Processing Tasks
Convolution kernels, such as sequence and tree kernels, are advantageous for both the concept and accuracy of many natural language processing (NLP) tasks. Experiments have, howev...
Jun Suzuki, Hideki Isozaki, Eisaku Maeda