Document clustering has been used as a core technique in managing vast amount of data and providing needed information. In on-line environments, generally new information gains mo...
This paper presents a comprehensive statistical analysis of workloads collected on data-intensive clusters and Grids. The analysis is conducted at different levels, including Virt...
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Conventional clustering methods typically assume that each data item belongs to a single cluster. This assumption does not hold in general. In order to overcome this limitation, w...
Andreas P. Streich, Mario Frank, David A. Basin, J...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...