We address the problem of robust clustering by combining data partitions (forming a clustering ensemble) produced by multiple clusterings. We formulate robust clustering under an ...
The development of areas such as remote and airborne sensing, location based services, and geosensor networks enables the collection of large volumes of spatial data. These datase...
Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints, namely exchanging two or more time points is not...
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
We describe the design and implementation of a new data layout scheme, called multi-dimensional clustering, in DB2 Universal Database Version 8. Many applications, e.g., OLAP and ...