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Knowledge Mining in Manufacturing and Management

Pawinee Boonyasopon, A. Riel


This paper presents intermediate results of a research study which investigates the potential of the use of text mining based approaches to capitalize on knowledge contained in research publications in the product development and manufacturing domain. The ultimate research target is to conceive a system which is able to motivate and facilitate researchers to collaborate, to help them get their publications cited, to improve their bibliographies, and thus to better capitalize on their own and related research. The capabilities of such a system shall go far beyond currently available full-text search based approaches. Departing from results obtained by the application of a particular text mining tool based on Latent Dirichlet Allocation (LDA) on a vast set of manufacturing research publications, the paper investigates alternative algorithmic approaches which promise to get rid of the shortcomings of the LDA-based implementation. It gives an outlook on further research steps that shall lead to an answer which approach is suitable for the application of knowledge mining in the product development and manufacturing research domain.


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