Scalable Visual Analytics of Massive Textual Datasets

M. Krishnan, S. Bohn, W. Cowley, V. Crow, J. Nieplocha
2007 2007 IEEE International Parallel and Distributed Processing Symposium  
This paper describes the first scalable implementation of a text processing engine used in visual analytics tools. These tools aid information analysts in interacting with and understanding large textual information content through visual interfaces. By developing a parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive datasets. The paper describes key elements of our parallelization approach and demonstrates
more » ... virtually linear scaling when processing multi-gigabyte data sets such as Pubmed. This approach enables interactive analysis of large datasets beyond capabilities of existing state-of-the art visual analytics tools.
doi:10.1109/ipdps.2007.370232 dblp:conf/ipps/KrishnanBCCN07 fatcat:tkcnjcravza5fm4r2awbn3wcqi