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» Hybrid Learning Scheme for Data Mining Applications
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GECCO
2006
Springer
214views Optimization» more  GECCO 2006»
13 years 11 months ago
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
SISAP
2009
IEEE
122views Data Mining» more  SISAP 2009»
14 years 2 months ago
Dynamic Spatial Approximation Trees for Massive Data
—Metric space searching is an emerging technique to address the problem of efficient similarity searching in many applications, including multimedia databases and other reposito...
Gonzalo Navarro, Nora Reyes
CAISE
2003
Springer
14 years 1 months ago
Hybrid Publish-Subscribe: A Compromise Approach for Large-Scale
Abstract. The purpose of this article is to propose a scalable, topologically and traffic-wise self-adapting approach to a publish/subscribe paradigm for supporting event-based app...
Roman Szarowski
SDM
2007
SIAM
104views Data Mining» more  SDM 2007»
13 years 9 months ago
Fast Multilevel Transduction on Graphs
The recent years have witnessed a surge of interest in graphbased semi-supervised learning methods. The common denominator of these methods is that the data are represented by the...
Fei Wang, Changshui Zhang
LREC
2010
115views Education» more  LREC 2010»
13 years 5 months ago
Mining Naturally-occurring Corrections and Paraphrases from Wikipedia's Revision History
Naturally-occurring instances of linguistic phenomena are important both for training and for evaluating automatic text processing. When available in large quantities, they also p...
Aurélien Max, Guillaume Wisniewski