Data Mining SIAM PresentationThis viewgraph document describes the data mining system developed at NASA Ames. Many NASA programs have large numbers (and types) of problem reports.These free text reports are written by a number of different people, thus the emphasis and wording vary considerably With so much data to sift through, analysts (subject experts) need help identifying any possible safety issues or concerns and help them confirm that they haven't missed important problems. Unsupervised clustering is the initial step to accomplish this; We think we can go much farther, specifically, identify possible recurring anomalies. Recurring anomalies may be indicators of larger systemic problems. The requirement to identify these anomalies has led to the development of Recurring Anomaly Discovery System (ReADS).
Document ID
20080010084
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Srivastava, Ashok (NASA Ames Research Center Moffett Field, CA, United States)
McIntosh, Dawn (NASA Ames Research Center Moffett Field, CA, United States)
Castle, Pat
Pontikakis, Manos
Diev, Vesselin (California Univ. Santa Cruz, CA, United States)
Zane-Ulman, Brett
Turkov, Eugene
Akella, Ram (California Univ. Santa Cruz, CA, United States)
Xu, Zuobing (California Univ. Santa Cruz, CA, United States)
Kumaresan, Sakthi Preethi (California Univ. Santa Cruz, CA, United States)