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AI
1999
Springer
13 years 7 months ago
Learning by Discovering Concept Hierarchies
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...
ICMCS
2009
IEEE
131views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Web image mining using concept sensitive Markov stationary features
With the explosive growth of web resources, how to mine semantically relevant images efficiently becomes a challenging and necessary task. In this paper, we propose a concept sens...
Chunjie Zhang, Jing Liu, Hanqing Lu, Songde Ma
ACCV
2009
Springer
14 years 2 months ago
Image-Set Based Face Recognition Using Boosted Global and Local Principal Angles
Face recognition using image-set or video sequence as input tends to be more robust since image-set or video sequence provides much more information than single snapshot about the ...
Xi Li, Kazuhiro Fukui, Nanning Zheng
IFIP12
2008
13 years 9 months ago
Agent Based Frequent Set Meta Mining: Introducing EMADS
In this paper we: introduce EMADS, the Extendible Multi-Agent Data mining System, to support the dynamic creation of communities of data mining agents; explore the capabilities of ...
Kamal Ali Albashiri, Frans Coenen, Paul H. Leng
IMCSIT
2010
13 years 5 months ago
Learning taxonomic relations from a set of text documents
This paper presents a methodology for learning taxonomic relations from a set of documents that each explain one of the concepts. Three different feature extraction approaches with...
Mari-Sanna Paukkeri, Alberto Pérez Garc&iac...