Effective management of knowledge assets is key to surviving in today's competitive business environment. This is particularly true for large organisations, where employees have difficulties identifying where or with whom the knowledge lies. Expertise is one of the most important knowledge assets and largely resides in the heads of employees. Many attempts have been made to help locate employees with the right expertise; however, the existing systems (often referred to as expertise finding systems) carry several flaws. In organisations, there are several potential sources where expertise evidence might be found. These sources have been used by the existing approaches to profile employees' expertise. Unfortunately, there has been limited research showing whether these sources contain useful evidence of expertise. Moreover, the majority of existing approaches have not been designed to integrate with the organisations' work practices; nor have they investigated the socio-ethical challenges associated with the adoption of such systems. Therefore, there is a need for expert finding systems that utilise useful sources of expertise and integrate into existing work practices. Through industry involvement, this research has explored and validated email content as a source for expertise profiling. This thesis provides an overview of the traditional and current approaches to expertise finding. The development and implementation of the EKE (Email Knowledge Extraction) system which tries to overcome the aforementioned challenges is presented. EKE has been evaluated by end-users from both industry and academia. The evaluation results suggest that EKE is a useful system that encourages participation, and that in many cases may assist in the management of knowledge within organisations.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:492821 |
Date | January 2008 |
Creators | Tedmori, Sara |
Publisher | Loughborough University |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://dspace.lboro.ac.uk/2134/3580 |
Page generated in 0.0022 seconds