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» Learning in FOL with a Similarity Measure
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ECAI
2000
Springer
15 years 6 months ago
Designing Clustering Methods for Ontology Building - The Mo'K Workbench
This paper describes Mo’K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo’K is intended to assist ontology de...
Gilles Bisson, Claire Nedellec, Dolores Cañ...
CORR
2002
Springer
79views Education» more  CORR 2002»
15 years 1 months ago
Technical Note: Bias and the Quantification of Stability
Research on bias in machine learning algorithms has generally been concerned with the impact of bias on predictive accuracy. We believe that there are other factors that should al...
Peter D. Turney
ICMLA
2009
14 years 11 months ago
Mahalanobis Distance Based Non-negative Sparse Representation for Face Recognition
Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some application...
Yangfeng Ji, Tong Lin, Hongbin Zha
ICIP
2010
IEEE
14 years 11 months ago
Automatic target recognition based on simultaneous sparse representation
In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extr...
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellap...
ESWS
2009
Springer
15 years 4 months ago
Hybrid Adaptive Web Service Selection with SAWSDL-MX and WSDL-Analyzer
Abstract. In this paper, we present an adaptive, hybrid semantic matchmaker for SAWSDL services, called SAWSDL-MX2. It determines three kinds of semantic service similarity with a ...
Matthias Klusch, Patrick Kapahnke, Ingo Zinnikus