Reusable knowledge pattern extraction from peer-to-peer communication elements
by Tapati Bandopadhyay, Pradeep Kumar, Anil K. Saini
International Journal of Value Chain Management (IJVCM), Vol. 5, No. 2, 2011

Abstract: Tacit knowledge embedded in various communication elements are highly unstructured, embedded in short message texts, and can be highly contextual thereby rendering generic English language thesaurus-based pattern recognition and extraction mechanisms relatively less useful. However, this embedded tacit knowledge is a significant source of context-specific, technical, problem-solving knowledge. Peer-to-peer communication threads have highly valuable problem-solution knowledge elements embedded in them. If these knowledge elements can be extracted, experiential knowledge in specific domains or technology areas can be significantly enhanced. In this paper, a process model has been designed, with algorithms developed and validated using appropriate examples, for extracting these reusable knowledge patterns from various peer-to-peer communication elements in any organisation or in the social network environment. Using this process model, the knowledge extraction can be partially or completely automated, depending on the context-specificity of the knowledge elements and therefore the requirements of specific thesaurus or term-dictionaries.

Online publication date: Thu, 26-Mar-2015

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