원문정보
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
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