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KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 6 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
CIKM
2004
Springer
15 years 10 months ago
Taxonomy-driven computation of product recommendations
Recommender systems have been subject to an enormous rise in popularity and research interest over the last ten years. At the same time, very large taxonomies for product classifi...
Cai-Nicolas Ziegler, Georg Lausen, Lars Schmidt-Th...
BMCBI
2007
178views more  BMCBI 2007»
15 years 6 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
IJAR
2010
105views more  IJAR 2010»
15 years 3 months ago
A tree augmented classifier based on Extreme Imprecise Dirichlet Model
In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet ...
G. Corani, C. P. de Campos
MVA
2011
336views Computer Vision» more  MVA 2011»
15 years 1 months ago
In-vehicle camera traffic sign detection and recognition
: In this paper we discuss theoretical foundations and a practical realization of a real-time traffic sign detection, tracking and recognition system operating on board of a vehicl...
Andrzej Ruta, Fatih Porikli, Shintaro Watanabe, Yo...