Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/...
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
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...
This paper presents a concurrent object model based on distributed recursive sets for data intensive applications that use complex, recursive data layouts. The set abstraction is ...
A key challenge in supporting data-driven scientific applications is the storage and management of input and output data in a distributed environment. In this paper, we describe a...
Stephen Langella, Shannon Hastings, Scott Oster, T...