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IDA
2006
Springer
15 years 6 months ago
Supporting bi-cluster interpretation in 0/1 data by means of local patterns
Clustering or co-clustering techniques have been proved useful in many application domains. A weakness of these techniques remains the poor support for grouping characterization. ...
Ruggero G. Pensa, Céline Robardet, Jean-Fra...
JCST
2008
138views more  JCST 2008»
15 years 6 months ago
Predicting Chinese Abbreviations from Definitions: An Empirical Learning Approach Using Support Vector Regression
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an em...
Xu Sun, Houfeng Wang, Bo Wang 0003
CORR
2007
Springer
113views Education» more  CORR 2007»
15 years 6 months ago
Virtual screening with support vector machines and structure kernels
Support vector machines and kernel methods have recently gained considerable attention in chemoinformatics. They offer generally good performance for problems of supervised classi...
Pierre Mahé, Jean-Philippe Vert
JDCTA
2008
115views more  JDCTA 2008»
15 years 6 months ago
Information Visualization Techniques and Decision Style: The Effects in Decision Support Environments
The importance of individual characteristics has been emphasized in the human computer interaction and information visualization (IV) literature. However, decision style, which is...
Nik Ghazali Nik Daud, Wan Adilah Wan Adnan, Nor La...
JMLR
2008
114views more  JMLR 2008»
15 years 6 months ago
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin