Earticle

초록

영어

The exhibition industry has showed steady growth in both terms of the size of an exhibition and the amount of money it generates. As the ubiquitous environment, there is much useful information for inferring visitors’preference.
However, the development and provision of such services have some issues. They are not designed as user-friendly systems and taken account of the preferences and interests of visitors. For satisfaction of visitors, exhibitions need to meet the needs for personalization. Therefore, we suggest a personalized booth recommendation methodology for real-time exhibition guidance in ubiquitous exhibition environment. In a computer supported ubiquitous learning environment, visitors’booth visiting path can play a key role for reasoning visitors’preference. In this study, by considering the booth visiting path of target visitors, we expect to reflect visitors’dynamic preference so that have improved accuracy compared to traditional Collaborative Filtering. Moreover, as we suggest a simple algorithm for fast predictions in recommender systems, we can also solve scalability problems.

목차

Abstract
 1. Introduction
 2. Related work
  2.1. Application of ubiquitous environment in exhibition
  2.2. Recommender systems considering the sequence
 3. Methodology
  3.1. Overview
  3.2. Preprocessing
  3.3. The recommendation process
 4. An illustrative example
  4.1. Preprocessing
  4.2. The recommendation process
 5. Summary and future work
 References

저자

• Hyun Sil Moon [ School of Business Administration, Kyunghee University ]
• Hyea Kyeong Kim [ School of Business Administration, Kyunghee University ]
• Jae Kyeong Kim [ School of Business Administration, Kyunghee University ]

참고문헌