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» Introduction to Pattern Recognition
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KDD
2005
ACM
181views Data Mining» more  KDD 2005»
16 years 5 months ago
Evaluating similarity measures: a large-scale study in the orkut social network
Online information services have grown too large for users to navigate without the help of automated tools such as collaborative filtering, which makes recommendations to users ba...
Ellen Spertus, Mehran Sahami, Orkut Buyukkokten
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
16 years 5 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 5 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
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
16 years 5 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
120
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KDD
2003
ACM
124views Data Mining» more  KDD 2003»
16 years 5 months ago
Information-theoretic co-clustering
Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingenc...
Inderjit S. Dhillon, Subramanyam Mallela, Dharmend...