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ICDM
2007
IEEE
97views Data Mining» more  ICDM 2007»
14 years 3 months ago
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
HIPC
2003
Springer
14 years 1 months ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
DAWAK
2010
Springer
13 years 9 months ago
Mining Closed Itemsets in Data Stream Using Formal Concept Analysis
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Anamika Gupta, Vasudha Bhatnagar, Naveen Kumar
IEEEICCI
2002
IEEE
14 years 1 months ago
Mining Fuzzy Rules in A Donor Database for Direct Marketing by a Charitable Organization
Given a donor database by a charitable organization in Hong Kong, we propose to use a new data mining technique to discover fuzzy rules for direct marketing. The discovered fuzzy ...
Keith C. C. Chan, Wai-Ho Au, Berry Choi
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
14 years 9 months ago
Reasoning about sets using redescription mining
Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of associa...
Mohammed Javeed Zaki, Naren Ramakrishnan