Abstract
The transfer of knowledge from academia to industry is of critical importance to both academics and industrialists. It can be argued that patent documents referring to a set of well-researched concepts may be used as a measure of such a transfer. Concepts are typically articulated as terms, and shared terms in research papers and patent documents are proposed as the monitoring index. 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. A corpus linguistic approach has been taken to research the changes in terminology that occurred in the development of Artificial Intelligence since 1936. We have examined the terminology used in a sample of journal papers and patents and found that the terminological preferences of the authors change over time. Biological models of growth have been applied to model the diachronic changes, and the results show that the growth of term usage and the transfer of knowledge may be modelled by using logistic growth techniques.