Constructing a web-based employee training expert system with data mining approach

Kuang Ku Chen, Mu Yen Chen, Hui Ju Wu, Yi Lung Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - The 9th IEEE International Conference on E-Commerce Technology; The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC/EEE 2007
Pages659-664
Number of pages6
DOIs
Publication statusPublished - 2007
Event9th IEEE International Conference on E-Commerce Technology; The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC/EEE 2007 - Tokyo, Japan
Duration: 2007 Jul 232007 Jul 26

Publication series

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

Conference

Conference9th IEEE International Conference on E-Commerce Technology; The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC/EEE 2007
Country/TerritoryJapan
CityTokyo
Period07-07-2307-07-26

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Computer Networks and Communications

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