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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 7 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»
15 years 10 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»
16 years 6 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»
16 years 21 days 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
16 years 19 days 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...