Mining Authoritativeness of Collaborative Innovation Partners

The global marketplace over the past decade has called for innovative products and cost reduction. This perplexing duality has led companies to seek external collaborations to effectively deliver innovative products to market. External collaboration often leads to innovation at reduced research and development expenditure. This is especially true of companies which find the most authoritative entity (usually a company or even a person) to work with. Authoritativeness accelerates development and research-to-product transformation due to the inherent knowledge of the authoritative entity. This paper offers a novel approach to automatically determine the authoritativeness of entities for collaboration. This approach automatically discovers an authoritative entity in a domain of interest. The methodology presented utilizes web mining, text mining, and generation of an authoritativeness metric. The concepts discussed in the paper are illustrated with a case study of mining the authoritativeness of collaboration partners for microelectromechanical systems (MEMS).

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