篇名 | Mining Association Rules between Education, Family Background and Earning |
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卷期 | 31:2 |
作者 | Chih Yen Chang 、 Ming Sang Chang |
頁次 | 056-069 |
關鍵字 | association rule mining 、 data mining 、 inequality 、 random forest similarity 、 socioeconomic status 、 EI 、 MEDLINE 、 Scopus |
出刊日期 | 202004 |
DOI | 10.3966/199115992020043102007 |
Education is widely regarding as the primary way to allocate the economic remuneration. Most people consider education as a mechanism that can sabotage the association of economic inequality. In this paper, we intend to propose a mechanism to investigate the determinants that take influence on one’s economic rewards by leveraging diverse data mining techniques, instead of using statistical methods solely. We found the determinants of one’s earning would vary depending on macro or micro perspectives which are rarely mentioned in other works. In macro view, it showed that the self-worth of a student played the most important role, followed by school practice and family background. In micro view, the sub-factors were investigated with six scenarios respectively. Our findings not only reflect the status-quo of society, but can be references in how background shapes one’s future.