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KDD
2003
ACM
129views Data Mining» more  KDD 2003»
14 years 9 months ago
Empirical comparisons of various voting methods in bagging
Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subj...
Kelvin T. Leung, Douglas Stott Parker Jr.
ICDM
2006
IEEE
214views Data Mining» more  ICDM 2006»
14 years 2 months ago
Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently however, we have been approached by Texas Commiss...
Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, X...
AUSDM
2008
Springer
230views Data Mining» more  AUSDM 2008»
13 years 11 months ago
Combining Structure and Content Similarities for XML Document Clustering
This paper proposes a clustering approach that explores both the content and the structure of XML documents for determining similarity among them. Assuming that the content and th...
Tien Tran, Richi Nayak, Peter Bruza
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 7 months ago
Laplacian Spectrum Learning
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
Pannagadatta K. Shivaswamy, Tony Jebara
KDD
2010
ACM
265views Data Mining» more  KDD 2010»
13 years 10 months ago
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Influence maximization, defined by Kempe, Kleinberg, and Tardos (2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influe...
Wei Chen, Chi Wang, Yajun Wang