posted on 2004-01-01, 00:00authored byJaime G. Carbonell, Eugene Fink, Chun Jin, Bora Cenk Gazen, J. Mathew, A. Saxena, S Ananthraman, D. Dietrich, G Mani, J. Tittle, P. Durbin
Project ARGUS is focused on helping an analyst explore massive, structured data. This scalable
exploration includes exact and partial match queries, monitoring hypotheses and discovery of novel
patterns in both static and streaming data. We provide these facilities within the context of an
analyst workbench interface called Data Explorer.
The remainder of this paper comprises three sections; a) a brief review of the methodology
employed within ARGUS for the detection of novelty within massive data, b) monitoring of
streaming data and a synopsis of the research originating out of the CMU team on the incremental
aggregation on multiple continuous queries, and, c) the development of an analyst workbench
environment, called ARGUS Data Explorer that has been developed by the teams from DYNAMiX
and ManTech CSEC. The ARGUS Data Explorer is currently being evaluated through the RDEC
environment/process as a precursor to possible deployment into live operating environments.