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Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search
Document ID
20060053332
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
McIntosh, Dawn
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
September 7, 2013
Publication Date
June 21, 2006
Subject Category
Documentation And Information Science
Meeting Information
Meeting: Data Mining Aplications in Aeronautics and Space Exploration Workshop
Location: Moffett Field, CA
Country: United States
Start Date: June 20, 2006
End Date: June 21, 2006
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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