Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
In this paper we analyze the I/O access patterns of a widely-used biological sequence search tool and implement two variations that employ parallel-I/O for data access based on PV...
Yifeng Zhu, Hong Jiang, Xiao Qin, David R. Swanson
Abstract-- This paper introduces a generalization of the Gravitational Clustering Algorithm proposed by Gomez et all in [1]. First, it is extended in such a way that not only the G...
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data in...
Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan ...