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BMCBI
2007
178views more  BMCBI 2007»
13 years 7 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
IJIS
2008
123views more  IJIS 2008»
13 years 7 months ago
Algorithms of nonlinear document clustering based on fuzzy multiset model
Abstract: Fuzzy multiset is applicable as a model of information retrieval because it has the mathematical structure which expresses the number and the degree of attribution of an ...
Kiyotaka Mizutani, Ryo Inokuchi, Sadaaki Miyamoto
SAMT
2007
Springer
117views Multimedia» more  SAMT 2007»
14 years 1 months ago
A Region Thesaurus Approach for High-Level Concept Detection in the Natural Disaster Domain
Abstract. This paper presents an approach on high-level feature detection using a region thesaurus. MPEG-7 features are locally extracted from segmented regions and for a large set...
Evaggelos Spyrou, Yannis S. Avrithis
MM
2005
ACM
122views Multimedia» more  MM 2005»
14 years 1 months ago
Image clustering with tensor representation
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
Xiaofei He, Deng Cai, Haifeng Liu, Jiawei Han
NIPS
2004
13 years 8 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...