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» A framework for mining interesting pattern sets
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KDD
2003
ACM
217views Data Mining» more  KDD 2003»
16 years 2 months ago
Algorithms for estimating relative importance in networks
Large and complex graphs representing relationships among sets of entities are an increasingly common focus of interest in data analysis--examples include social networks, Web gra...
Scott White, Padhraic Smyth
98
Voted
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
15 years 8 months ago
Non-redundant Multi-view Clustering via Orthogonalization
Typical clustering algorithms output a single clustering of the data. However, in real world applications, data can often be interpreted in many different ways; data can have diff...
Ying Cui, Xiaoli Z. Fern, Jennifer G. Dy
CLA
2004
15 years 3 months ago
Emulating a Cooperative Behavior in a Generic Association Rule Visualization Tool
Traditional framework for mining association rules has pointed out the derivation of many redundant rules. In order to be reliable in a decision making process, such discovered rul...
I. Nsir, Sadok Ben Yahia, Engelbert Mephu Nguifo
114
Voted
SIGIR
2003
ACM
15 years 7 months ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
15 years 8 months ago
Finding Maximal Fully-Correlated Itemsets in Large Databases
—Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. Much previous research focuses on finding ...
Lian Duan, William Nick Street