Reusable knowledge pattern extraction from peer-to-peer communication elements. (24th August 2011)

• Record Type: Journal Article
• Authors: Bandopadhyay, Tapati; Kumar, Pradeep; Saini, Anil K.
• Is Part Of: International journal of value chain management. Volume 5:Number 2(2011)
• Page Start: 151
• Page End: 158
• Publication Date: 2011-08-24
• Subjects: tacit knowledge -- knowledge extraction -- unstructured knowledge -- communication elements; Business logistics -- Periodicals; 658.7
• Languages: English
• ISSNs: 1741-5357

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.