Authors: Tapati Bandopadhyay, Pradeep Kumar, Anil K. Saini
Addresses: Narsee Monjee Institute of Management Studies, Swastik Manandi Arcade 401/2, SC Road, Shesadri Road, Bangalore, Karnataka – 560 020, India. ' Narsee Monjee Institute of Management Studies, VL Mehta Road, Vile Parle (W) Mumbai – 400 056, India. ' University School of Management Studies, GGS IP University, Kashmere Gate, Delhi – 110 006, India
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.
Keywords: tacit knowledge; knowledge extraction; unstructured knowledge; communication elements; process modelling; reusable knowledge patterns; peer-to-peer communication; P2P communication.
International Journal of Value Chain Management, 2011 Vol.5 No.2, pp.151 - 158
Published online: 23 Aug 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article