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Abstract:
A feasibility study was conducted to determine whether the sublanguage methodology of NLP could analyze and represent the vital information contained in trouble tickets’ ungrammatical text and to explore various knowledge mining approaches to render the data contained in these documents accessible for analysis and prediction. Experiments showed that the linguistic characteristics of trouble tickets fit the sublanguage theoretical framework, thus enabling NLP systems to tap into the unrealized value of trouble ticket data.