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» Probing Knowledge in Distributed Data Mining
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KAIS
2008
99views more  KAIS 2008»
13 years 7 months ago
Privacy-preserving SVM classification
Classical data mining algorithms implicitly assume complete access to all data, either in centralized or federated form. However, privacy and security concerns often prevent sharin...
Jaideep Vaidya, Hwanjo Yu, Xiaoqian Jiang
KDD
2003
ACM
210views Data Mining» more  KDD 2003»
14 years 8 months ago
Privacy-preserving k-means clustering over vertically partitioned data
Privacy and security concerns can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery, if done correctly, can alleviate this problem. The key ...
Jaideep Vaidya, Chris Clifton
HIPC
2003
Springer
14 years 26 days 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...
IJCAI
2003
13 years 9 months ago
Distributed Clustering Based on Sampling Local Density Estimates
Huge amounts of data are stored in autonomous, geographically distributed sources. The discovery of previously unknown, implicit and valuable knowledge is a key aspect of the expl...
Matthias Klusch, Stefano Lodi, Gianluca Moro
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
11 years 10 months ago
Unsupervised feature selection for linked social media data
The prevalent use of social media produces mountains of unlabeled, high-dimensional data. Feature selection has been shown effective in dealing with high-dimensional data for eï¬...
Jiliang Tang, Huan Liu