Text Classification for Mining Massive Report Data REGINA LIU Rutgers University Abstract: Text classification has become an indispensable tool for mining massive streaming textual data. Some statistical textual classification methods will be discussed and applied to the analysis of aviation inspection reports. There are massive numbers of aviation inspection reports collected by the FAA each year in the USA. These reports document findings from aviation surveillance inspections as well as aircraft accident or incident investigations. Applying text classification to the mining of these reports can show that the text classification methodology should be a critical element of the aviation safety decision support system. The performance of some existing text classification models will be evaluated in terms of misclassification rates. Further breakdowns of the misclassification rates and related findings from the dataset suggest ways for improving data quality and for gathering information which are more pertinent for filing inspection reports.