Abstract
This paper describes exploratory research on the application of computerized text analysis techniques to all U.S. engineering doctoral dissertation abstracts dated 1981, 1986, and 1991. Experts were utilized to categorize abstracts by industrial relevance, and to identify appropriate non-technology-specific word indicators within the abstracts. Word frequency and cluster analysis techniques were also explored for their potential utility in identifying technology-related work indicators of industrial relevance. The results of this work suggest that text analysis of engineering dissertation abstracts holds potential utility for identifying industrially relevant university-based engineering research, when used in conjunction with expert input and feedback.
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