Commenced in January 2007
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Paper Count: 32129
Discovery and Capture of Organizational Knowledge from Unstructured Information

Authors: J. Gu, W.B. Lee, C.F. Cheung, E. Tsui, W.M. Wang


Knowledge of an organization does not merely reside in structured form of information and data; it is also embedded in unstructured form. The discovery of such knowledge is particularly difficult as the characteristic is dynamic, scattered, massive and multiplying at high speed. Conventional methods of managing unstructured information are considered too resource demanding and time consuming to cope with the rapid information growth. In this paper, a Multi-faceted and Automatic Knowledge Elicitation System (MAKES) is introduced for the purpose of discovery and capture of organizational knowledge. A trial implementation has been conducted in a public organization to achieve the objective of decision capture and navigation from a number of meeting minutes which are autonomously organized, classified and presented in a multi-faceted taxonomy map in both document and content level. Key concepts such as critical decision made, key knowledge workers, knowledge flow and the relationship among them are elicited and displayed in predefined knowledge model and maps. Hence, the structured knowledge can be retained, shared and reused. Conducting Knowledge Management with MAKES reduces work in searching and retrieving the target decision, saves a great deal of time and manpower, and also enables an organization to keep pace with the knowledge life cycle. This is particularly important when the amount of unstructured information and data grows extremely quickly. This system approach of knowledge management can accelerate value extraction and creation cycles of organizations.

Keywords: Knowledge-Based System, Knowledge Elicitation, Knowledge Management, Taxonomy, Unstructured Information Management

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[1] C.F. Cheung, W.B. Lee, W.M. Wang, Y. Wang & W.M. Yeung. "A multi-faceted and automatic knowledge elicitation system (MAKES) for managing unstructured information", Expert Systems with Applications, 2011, vol. 38, pp. 5245 - 5258D.
[2] D. Hatch, "Data Management 2.0: Making Sense of Unstructured Data", Aberdeen Group Benchmark Report, Jul. 2007
[3] C. Moore, "Diving into Data: companies aim to control the rising tide of unstructured data and gain a strategic edge", InfoWorld,, Oct. 2002 (Accessed 20.3.10)
[4] J. D. Morris, "Unstructured information management - what you don-t know can hurt you!", Ezine Articles, Management--- What-You-Dont-Know-Can-Hurt-You!&id=1656140, Nov. 2008 (Accessed 20.3.10)
[5] C.C. Shilakes and J. Tylman, "Enterprise Information Portals", Merrill Lynch, 16 November, 1998.
[6] W. M. Wang; C. F. Cheung; W. B. Lee & S. K. Kwok, "Self-associated concept mapping for representation, elicitation and inference of knowledge", Journal of knowledge-based systems, 2008, vol. 21, pp. 52-61
[7] W.M. Wang & C.F. Cheung, "A narrative-based reasoning with applications in decision support for social service organizations", Expert Systems with Applications, 2011, vol. 38, pp. 3336 - 3345
[8] J. K., Waters, "Managing unstructured information", Application Development Trends Articles,, Jan. 2005 (Accessed 02.10.10)