This paper investigates the applicability of distributed clustering technique, called RACHET [1], to organize large sets of distributed text data. Although the authors of RACHET c...
Incremental hierarchical text document clustering algorithms are important in organizing documents generated from streaming on-line sources, such as, Newswire and Blogs. However, ...
In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
−Document clustering has become an increasingly important task in analyzing huge numbers of documents distributed among various sites. The challenging aspect is to analyze this e...
A distributed memory parallel version of the group average Hierarchical Agglomerative Clustering algorithm is proposed to enable scaling the document clustering problem to large c...
Rebecca Cathey, Eric C. Jensen, Steven M. Beitzel,...