Aprior算法的改进及其在高职学生就业中的应用

Improved Apriori Algorithm and Its Application in Higher Vocational Students' Employment

Apriori算法是一种最具有影响力的挖掘布尔关联规则频繁项集的算法。然而,在产生频繁项集时,需要多次扫描事务数据库,并产生庞大的候选集。为了降低算法的时间复杂度,提高程序运行效率,提出了一种改进的Apriori算法。同时,以某一高职院校中已毕业学生和在校生的就业信息为基础,建立了就业事务数据库,运用改进的Apriori算法对就业数据进行处理,产生了频繁项集。根据最小支持度和最小置信度的定义,找出强关联规则。并引入重要性对强关联规则进行分析,发现具有实际意义的信息,为高职学校就业指导提供决策,为学生就业提供了若干意见。

Apriori algorithm is one of the most influential algorithms of mining Boolean association rules frequent itemsets. However, in generating frequent itemsets, we need scan transaction database frequently, and generate a large of candidate sets. In order to reduce the time complexity of the algorithm, and improve the running efficiency of the program, this paper puts forward a kind of improved Apriori algorithm. In this paper, based on the employment information of higher vocational students, we build an employment transaction database, and process the employment data using the improved Apriori algorithm, to generate frequent itemsets. Finally, in terms of the minimum support and minimum confidence, we find the strong association rules from the frequent sets. Then, we introduce the importance to analyze the strong association, find out the hidden patterns, and discover the practical meaning information, to provide higher vocational students＇ employment guide with decision-making and suggestion.