CAJ | 학술논문

关联规则是数据挖掘领域中最重要的研究内容,能够在数据库中发现频繁模式和关联知识。对关联规则及其相关挖掘算法Apriori进行了分析,指出了Apriori算法存在的缺点。通过基于预处理的改进Apriori算法在高校教学评价中的应用,说明数据挖掘过程,分析挖掘结果,最后指出了未来的研究方向。
관련규칙시수거알굴영역중최중요적연구내용,능구재수거고중발현빈번모식화관련지식。대관련규칙급기상관알굴산법Apriori진행료분석,지출료Apriori산법존재적결점。통과기우예처리적개진Apriori산법재고교교학평개중적응용,설명수거알굴과정,분석알굴결과,최후지출료미래적연구방향。
Association rules which are considered the most important aspect in the research of data mining can find the frequent pattern and the relevant algorithm. This paper analyzed the relevant algorithm of Apriori and found some weaknesses existing in the rules. In order to illustrate the process of data mining and analyze the result, the application of the preprocessing improved Apriori Algorithm to the teaching evaluation in higher education was taken as an example. The paper finally give some suggestions for the future research in this field.