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PAISI
2010
Springer
14 years 9 months ago
Efficient Privacy Preserving K-Means Clustering
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...
FLAIRS
2004
15 years 1 months ago
Personalization Using Hybrid Data Mining Approaches in E-Business Applications
Effective personalization is greatly demanded in highly heterogeneous and diverse e-commerce domain. In our approach we rely on the idea that an effective personalization techniqu...
Olena Parkhomenko, Yugyung Lee, Chintan Patel
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
15 years 12 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
CCGRID
2006
IEEE
15 years 5 months ago
Statistical Data Reduction for Efficient Application Performance Monitoring
There is a growing need for systems that can monitor and analyze application performance data automatically in order to deliver reliable and sustained performance to applications....
Lingyun Yang, Jennifer M. Schopf, Catalin Dumitres...
CORR
1998
Springer
87views Education» more  CORR 1998»
14 years 11 months ago
Word Clustering and Disambiguation Based on Co-occurrence Data
We address the problem of clustering words (or constructing a thesaurus) based on co-occurrence data, and using the acquired word classes to improve the accuracy of syntactic disa...
Hang Li, Naoki Abe