Cloud-based clustering of text documents using the GHSOM algorithm on the GridGain platform
Martin Sarnovský, Z. Ulbrik · 2013
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.