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» Learning the Kernel Matrix for XML Document Clustering
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AAAI
2008
13 years 10 months ago
Multi-View Local Learning
The idea of local learning, i.e., classifying a particular example based on its neighbors, has been successfully applied to many semi-supervised and clustering problems recently. ...
Dan Zhang, Fei Wang, Changshui Zhang, Tao Li
SYNASC
2007
IEEE
136views Algorithms» more  SYNASC 2007»
14 years 1 months ago
Wikipedia-Based Kernels for Text Categorization
In recent years several models have been proposed for text categorization. Within this, one of the widely applied models is the vector space model (VSM), where independence betwee...
Zsolt Minier, Zalan Bodo, Lehel Csató
ICDAR
2011
IEEE
12 years 7 months ago
Subgraph Spotting through Explicit Graph Embedding: An Application to Content Spotting in Graphic Document Images
—We present a method for spotting a subgraph in a graph repository. Subgraph spotting is a very interesting research problem for various application domains where the use of a re...
Muhammad Muzzamil Luqman, Jean-Yves Ramel, Josep L...
ICPPW
2002
IEEE
14 years 15 days ago
Hebbian Algorithms for a Digital Library Recommendation System
generally meta-data, so that documents on any specific subject can be transparently retrieved. While quality control can in principle still rely on the traditional methods of peer-...
Francis Heylighen, Johan Bollen
BMCBI
2010
155views more  BMCBI 2010»
13 years 7 months ago
A flexible R package for nonnegative matrix factorization
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Renaud Gaujoux, Cathal Seoighe