Earticle

초록

영어

To date, most e-learning systems have not reflected emotion of users effectively as against off-line learning (system) that has sufficiently considered it. They might cause several prob-lems hindering e-learning from effectiveness. Overcoming this weakness, we introduce a methodology that measures user’s brain wave and recommends learning content to user based on it. In this paper, we assume that a person would have similar tendency with some-one whose brain wave patterns are like his, and use it for recommendation of learning con-tent type. As a technique for our experiment, we use kNN-Recommendation, learning content type recommendation system, based on brain wave data that appears in studying. Our system can solve cold-start problem that occurs in typical recommendation system and we addition-ally propose harmony value for better accuracy of recommendation that is calculated with recommended values from preceding our profile based recommendation system. We check advanced performance using several experiments.

목차

Abstract
 1. Introduction
 2. Learning Content Type Recommendation Using Brain Wave and User Profile
  2.1. Data Set
  2.2. Recommendation Algorithm
 3. Performance Evaluation
 4. Conclusion
 Acknowledgements
 References

키워드

저자

• Kyung suk Jung [ Division of Computer Science and Engineering, Hanyang University ]
• Yong suk Choi [ Division of Computer Science and Engineering, Hanyang University ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605