利用标准SQL查询挖掘多值型关联规则及其评价

关联规则是数据挖掘中一种重要的模式，目前对布尔型关联规则的挖掘算法研究得比较多，利用标准SQL功能，易于开发，运行速度快，安全可靠性强等优点，来实现多值型关联规则的挖掘具有比较好的性能，首先利用语言场理论对连续属性进行离散化，然后利用SQL对Apriori算法进行改进来实现关联规则的挖掘，另外利用主观Bayes方法中的LS充分性因子对挖掘出来的规则进行评价，该算法应用于庐江虫害数据库，结果显示它具有快速，有效，易开发，适用范围广等优点。

MINING QUANTITATIVE ASSOCIATION RULES WITH STANDARD SQL QUERIES AND IT'S EVALUATION

Association rule is an important model in data mining. Currently, more research work is done on the algorithm of mining boolean association rules than on the algorithm of quantitative association rules. With standard SQL, which has the advantages of powerful function, easy development, quick running speed, and strong reliability etc , to implement the quantitative association rules mining can result in good performance. Firstly, quantitative attribute needs to be dispersed with language field theory. Then association rules are mined by improving Apriori algorithm with SQL. Additionly, the association rules are evaluated with the sufficiency gene LS of subjectivity Bayes reasoning. This algorithm has been applied to the Lujiang Insect Pests Database, and the experiment result shows that this algorithm is quick, effective, easy to develop, and can be widely applied.