Hypothesis Formation and Tracking in ARGUS

Autor: B. Cenk Gazen, Carbonell, Jaime G., Hayes, Philip J., Jin, Chun, Fink, Eugene
Rok vydání: 2001
Předmět:
DOI: 10.1184/r1/6606239.v1
Popis: New Hypothesis formation may be an analyst-initiated activity, an automated process whereby a novel trend is discovered and tracked, or a hybrid one. In the hybrid case, the system offers its discovery of novel, potentially interesting patterns for analyst review, leading to new hypothesis being formed and tracked, or to discarding the novelty as coincidental or uninteresting. The ARGUS project assumes the third paradigm, where a combination of analysis of massive data – both historical and real-time streams – leads to automated creation of potential hypothesis for analysts to consider, discard, embellish, combine, and/or instruct ARGUS to track as a new persistent interest profile.
Databáze: OpenAIRE