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Text · dataset · 2025

Anomaly Detection with Text Mining

Listed in NASA Data Portal

Many existing complex space systems have a significant amount of historical maintenance and problem data bases that are stored in unstructured text forms.

Description

The problem that we address in this paper is the discovery of recurring anomalies and relationships between problem reports that may indicate larger systemic problems. We will illustrate our techniques on data from discrepancy reports regarding software anomalies in the Space Shuttle.

These free text reports are written by a number of different people, thus the emphasis and wording vary considerably. With Mehran Sahami from Stanford University, I'm putting together a book on text mining called "Text Mining: Theory and Applications" to be published by Taylor and Francis.

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Inferred from text
Data mining and knowledge discovery 76% · Text 75%
Provenance · 1 source records, 8 field assertions
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NASA Data Portal0a7fe2c2-920d-49c6-b04d-20e7b33c884110 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:field:460502enrichment · data nasa govtaxonomy-embedding@1.1.0title+keywords+description (76%)
concepts[modality].local:modality:textenrichment · data nasa govkeyword-concept-rules@1.0.0title+description (75%)
created_datesource · data nasa govconnector:data_nasa_gov@1.0.0
descriptionsource · data nasa govconnector:data_nasa_gov@1.0.0/notes
license_textsource · data nasa govconnector:data_nasa_gov@1.0.0
publication_datesource · data nasa govconnector:data_nasa_gov@1.0.0
titlesource · data nasa govconnector:data_nasa_gov@1.0.0/title
updated_datesource · data nasa govconnector:data_nasa_gov@1.0.0