Clustering has been one of the most popular approaches used in gene expression data analysis. A clustering method is typically used to partition genes according to their similarity...
We present a new method for spectral clustering with paired data based on kernel canonical correlation analysis, called correlational spectral clustering. Paired data are common i...
Monitoring cluster evolution in data streams is a major research topic in data streams mining. Previous clustering methods for evolving data streams focus on global clustering res...
Liang Tang, Chang-jie Tang, Lei Duan, Chuan Li, Ye...
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
This paper presents a publish/subscribe based asynchronous remote method invocation framework (PARMI) aiming to improve performance and programming flexibility. PARMI enables high-...