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» Data Mining via Support Vector Machines
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ICML
2008
IEEE
15 years 10 months ago
Robust matching and recognition using context-dependent kernels
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabariso...
WCE
2007
14 years 11 months ago
A Comparison of Classification Techniques for Technical Text Passages
— Our work explores the use of several text categorization techniques for classification of manufacturing quality defect and service shop data sets into fixed categories. Althoug...
Mark M. Kornfein, Helena Goldfarb
ACL
2003
14 years 11 months ago
Fast Methods for Kernel-Based Text Analysis
Kernel-based learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinatio...
Taku Kudo, Yuji Matsumoto
BMCBI
2008
146views more  BMCBI 2008»
14 years 10 months ago
ProLoc-GO: Utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization
Background: Gene Ontology (GO) annotation, which describes the function of genes and gene products across species, has recently been used to predict protein subcellular and subnuc...
Wen-Lin Huang, Chun-Wei Tung, Shih-Wen Ho, Shiow-F...
RIAO
2007
14 years 11 months ago
XML Fragments Extended with Database Operators
XML documents represent a middle range between unstructured data such as textual documents and fully structured data encoded in databases. Typically, information retrieval techniq...
Yosi Mass, Dafna Sheinwald, Benjamin Sznajder, Siv...