Earticle

초록

영어

In the healthcare literature, happiness has been neglected as an important research issue. However, it seems clear that happiness becomes more important in research agenda as societies grow older. It is well known that happiness is related with various kinds of factors. Therefore, managing happiness requires careful handling of a number of related factors in a very systematic and organized way. In this sense, this study proposes General Bayesian Network (GBN) approach in order to extract causal knowledge about happiness from the analysis of the related factors. By using Friends-and-Family dataset, we performed GBN-based scenario analyses to answer sophisticated questions about happiness. The empirical results showed that GBN proved to have huge potentials in handling well-ness problems in the field of health informatics.

목차

Abstract
 1. Introduction
 2. System Model and Methods
  2.1. Data Set
  2.2. Benchmarking Classifiers
  2.3. Scenario-Based Analysis
 3. Results
  3.1. Experiment 1
  3.2. Experiment 2: Scenario-Based Analysis
 3. Concluding Remarks
 Acknowledgement
 References

키워드

저자

• Jae Mun Sim [ Research Professor at SKK Business School Researcher at Health Mining Research Institute Sungkyunkwan University, Seoul 110-745, Republic of Korea ]
• Kun Chang Lee [ Professor, SKK Business School Director, Health Mining Research Institute Sungkyunkwan University, Seoul 110-745, Republic of Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605