Cloud-based clustering of text documents using the GHSOM algorithm on the GridGain platform

Abstract

This paper provides an overview of our research activities aimed on efficient use of distributed computing concepts for text-mining tasks. Work presented within this paper describes the GHSOM (Growing Hierarchical Self-Organizing Maps) algorithm for clustering of text documents and proposes the design and implementation of distributed version of this approach. Proposed implementation is based on JBOWL framework as a base for text mining. For distribution we used MapReduce paradigm implemented within the GridGain framework, which was used as a cloud application platform. Experiments were performed on standard Reuters dataset and for testing purposes we decided to use a simple private cloud infrastructure.