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...
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...
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...
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...
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...