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Articles

Knowledge search with unclear or ambiguous descriptions: a functional framework for knowledge trading platform

Pages 655-670 | Received 14 Aug 2010, Accepted 26 May 2011, Published online: 01 Mar 2012
 

Abstract

In the current era of the innovation economy, online trading or exchanging knowledge can introduce creativity and new technologies, thereby lowering innovation costs and expediting R&D of knowledge creation and product. However, descriptions of knowledge products are often more complex and abstract than those of physical products. To design a function-completed knowledge trading platform and to enable accurate searches for required knowledge on the platform even with unclear or ambiguous descriptions, knowledge and requirement representation structure models are needed by sellers to clearly describe knowledge features and by buyers to identify required knowledge. This study applied the knowledge-commercialised business model in the design of a functional framework for an online knowledge trading platform. The proposed similarity measurement algorithm for realising online knowledge trading enables precise searches of knowledge based on abstract requirement descriptions. The algorithm comprises one direct and seven indirect similarity computing functions based on different relationships between abstract concepts in both knowledge and requirement representation structure models. The framework and knowledge similarity measurement proposed in this study can be used to implement functionally complete k-commerce websites and to match knowledge requesters with providers.

Acknowledgement

The author thanks the National Science Council of the Republic of China, Taiwan, for financially supporting this research under Contract No. NSC 98-2221-E-343-009.

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