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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 10 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
PKDD
1999
Springer
90views Data Mining» more  PKDD 1999»
14 years 1 months ago
Learning from Highly Structured Data by Decomposition
This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
René MacKinney-Romero, Christophe G. Giraud...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 9 months ago
BBM: bayesian browsing model from petabyte-scale data
Given a quarter of petabyte click log data, how can we estimate the relevance of each URL for a given query? In this paper, we propose the Bayesian Browsing Model (BBM), a new mod...
Chao Liu 0001, Christos Faloutsos, Fan Guo
INCDM
2009
Springer
96views Data Mining» more  INCDM 2009»
14 years 3 months ago
Ordinal Evaluation: A New Perspective on Country Images
We present a novel use of ordinal evaluation (OrdEval) algorithm as a promising technique to study various marketing phenomena. OrdEval algorithm has originated in data mining and ...
Marko Robnik-Sikonja, Kris Brijs, Koen Vanhoof
CEC
2008
IEEE
14 years 3 months ago
Distributed multi-relational data mining based on genetic algorithm
—An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules i...
Wenxiang Dou, Jinglu Hu, Kotaro Hirasawa, Gengfeng...