Reusable knowledge pattern extraction from peer-to-peer communication elements
Tapati Bandopadhyay, Pradeep Kumar, Anil Kumar Saini · International Journal of Value Chain Management · 2011
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.