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» Distributed Data Mining Models as Services on the Grid
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ERCIMDL
2004
Springer
104views Education» more  ERCIMDL 2004»
15 years 12 months ago
Servicing the Federation: The Case for Metadata Harvesting
The paper presents a comparative analysis of data harvesting and distributed computing as complementary models of service delivery within large-scale federated digital libraries. I...
Fabio Simeoni
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
14 years 9 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
IWNAS
2008
IEEE
16 years 25 days ago
Accurate Performance Modeling and Guidance to the Adoption of an Inconsistency Detection Framework
With the increased popularity of replica-based services in distributed systems such as the Grid, consistency control among replicas becomes more and more important. To this end, I...
Yijun Lu, Xueming Li, Hong Jiang
SADM
2010
141views more  SADM 2010»
15 years 1 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
16 years 1 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey