Earticle

초록

영어

Recently, the exhibition industry has developed rapidly with the development of information technologies. Most exhibitors in an exhibition plan and deploy many events that may provide advantages to visitors as a method of effective promotion. The growth and propagation of wireless technologies is a powerful marketing tool for exhibitors. However, exhibitors still rely on domain experts who are costly and time consuming because of the manual knowledge input procedure. Moreover, it is prone to biases and errors and not suitable for managing fast-growing and tremendous amounts of data that far exceed a human's ability to comprehend. To overcome these problems, data mining technology may be a great alternative, but it needs to be fit to each exhibition. This study uses data mining technology with the Predictive Model Markup Language (PMML) to suggest a system that supports intelligent services and that improves stakeholder satisfaction. This system provides advantages to the exhibitor, show organizer, and system designer, and is first enhanced by integrating data mining technologies through the knowledge of exhibition experts. Second, using the PMML, the system can automate the process of applying data mining models to solve real-time processing problems in the exhibition environment.

목차

Abstract
 Ⅰ. Introduction
 Ⅱ. Related Work
 Ⅲ. Procedure of IERMS
 Ⅳ. Applications of IERMS
  4.1 System Architecture
  4.2 Knowledge Pool
  4.3 Data Mining Modeling
  4.4 IERMS
 Ⅴ. Conclusion
 

키워드

저자

• Hyun Sil Moon [ School of Management, Kyung Hee University, Korea ]
• Yoon Ho Cho [ Professor, School of Business Administration, Kook Min University, Korea ]
• Jae Kyeong Kim [ Professor, School of Management, Kyung Hee University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Asia Pacific Journal of Information Systems

• 간기

  계간

• pISSN

  2288-5404

• eISSN

  2288-6818

• 수록기간

  1990~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 325 DDC 658