Advanced text clustering algorithm for aircraft applications

CaseBank provides a service called ChronicX™ to the airline industry for the purpose of detecting and managing repeat defects, i.e. faults that have eluded resolution repeatedly. Each night, airlines upload their raw maintenance records to the CaseBank server. ChronicX applies text mining methods to eliminate irrelevant records, and search for defects that are repeat occurrences of defects previously reported. These are assembled into clusters, each of which is called a ‘chronic’. ChronicX performs reasonably well, but it has limitations that we believe can be improved.

Intern: 
Nan Jiang
Faculty Supervisor: 
Dr. Jimmy Huang
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