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Key developments in science and engineering are usually signalled by the introduction of new terms and the exclusion of established ones; this change in the terminology may be construed as a change in the knowledge in that field. Early identification of these changes may provide opportunities for innovation and enhance an organisation s competitive intelligence. This book covers traditional approaches of monitoring the process of innovation and first reviews the philosophical ideas and perspectives on knowledge invention and growth, and details the intrinsic relationship between language and knowledge. The process of scientific discovery is described, and existing models that support the innovation process are evaluated, including scientometrics methods, the Redwine and Riddle model, and Moore s Technology Adoption Life Cycle. A corpus linguistic approach has been taken to research the changes in terminology that occurred in the development of Artificial Intelligence since 1936 and biological models of growth have been applied to model the diachronic changes. This analysis will be of interest to professionals in innovation management and researchers of corpus linguistics.
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