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Constructing a Web-based Employee Training Expert System with Data Mining Approach

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4 Author(s)
Kuang-Ku Chen ; National Changhua University of Education ; Mu-Yen Chen ; Hui-Ju Wu ; Yi-Lung Lee

Knowledge management (KM) is an important strategy in business management and competition in 21st century. Companies must manage their valuable knowledge and experience more aggressively to enhance competitive advantage and human resource management (HRM). In this paper, we present a web-based training system named ETES - employee training expert system and the methodologies of its implementation. ETES applied rule-based expert system technology to infer the learning type for employees. Moreover, ETES uses association rule mining to find training strategies and learning map for personal learning. Besides, ETES provides different training materials for employees according to their learning aptitudes, records and occupations. The system has been tested and is now in pilot use by Teraauto Corporation which is a high-profits listed securities company in Taiwan.

Published in:

The 9th IEEE International Conference on E-Commerce Technology and The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services (CEC-EEE 2007)

Date of Conference:

23-26 July 2007