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ICDM
2008
IEEE
92views Data Mining» more  ICDM 2008»
14 years 3 months ago
A Shrinkage Approach for Modeling Non-stationary Relational Autocorrelation
Recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances indi...
Pelin Angin, Jennifer Neville
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
14 years 9 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher
ICDM
2005
IEEE
137views Data Mining» more  ICDM 2005»
14 years 2 months ago
Leveraging Relational Autocorrelation with Latent Group Models
The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values...
Jennifer Neville, David Jensen
KDD
2003
ACM
217views Data Mining» more  KDD 2003»
14 years 9 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
ICDM
2003
IEEE
99views Data Mining» more  ICDM 2003»
14 years 1 months ago
Simple Estimators for Relational Bayesian Classifiers
In this paper we present the Relational Bayesian Classifier (RBC), a modification of the Simple Bayesian Classifier (SBC) for relational data. There exist several Bayesian classif...
Jennifer Neville, David Jensen, Brian Gallagher