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» Question classification using support vector machines
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132
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AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
15 years 6 months ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang
131
Voted
SCAI
2008
15 years 4 months ago
Defect Prediction in Hot Strip Rolling Using ANN and SVM
One of the largest factors affecting the loss for steel manufacturing are defects in the steel strips produced. Therefore the prediction of these defects forehand would be very im...
Manu Hietaniemi, Ulla Elsilä, Perttu Laurinen...
141
Voted
ECML
2006
Springer
15 years 6 months ago
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
Alessandro Moschitti
111
Voted
PRL
2006
114views more  PRL 2006»
15 years 2 months ago
Incremental training of support vector machines using hyperspheres
In the conventional incremental training of support vector machines, candidates for support vectors tend to be deleted if the separating hyperplane rotates as the training data ar...
Shinya Katagiri, Shigeo Abe
104
Voted
ICPR
2004
IEEE
16 years 3 months ago
Statistical Classification of Raw Textile Defects
In this paper, the problem of classification of defects occurring in a textile manufacture is addressed. A new classification scheme is devised in which different features, extrac...
Ivan A. Rossi, Manuele Bicego, Vittorio Murino