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» Discovering Classification from Data of Multiple Sources
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126
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RCIS
2010
15 years 6 days ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
ICAI
2004
15 years 3 months ago
A Comparison of Resampling Methods for Clustering Ensembles
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
104
Voted
DKE
2006
138views more  DKE 2006»
15 years 1 months ago
Using the uni-level description (ULD) to support data-model interoperability
We describe a framework called the Uni-Level Description (ULD) for accurately representing information from a broad range of data models. The ULD extends previous metadata-model a...
Shawn Bowers, Lois M. L. Delcambre
EUROMED
2010
15 years 11 days ago
Architectural Heritage Online: Ontology-Driven Website Generation for World Heritage Sites in Danger
We introduce an online knowledge base for semantic representation and annotation of a world heritage site in danger. For this purpose we designed ontology inside the protégé tool...
Elham Andaroodi, Asanobu Kitamoto
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
16 years 2 months ago
Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers
Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...
Vincent Yan Fu Tan, See-Kiong Ng