基于灰色关联分析的Apriori算法的研究及应用

Research and Application of Apriori Algorithm Based on Gray Relational Analysis

关联分析是一种重要的数据挖掘技术。文中结合房地产行业的特点,将关联分析方法应用于对消费者购房行为的研究中。传统的关联规则挖掘算法-Apriori算法在实际应用中存在着计算量大、挖掘效率低、产生大量不相关的关联规则等问题。为了减少计算量、提高挖掘效率、发现有价值的关联规则,提出了一种灰色关联度分析算法和Apriori算法结合的研究方法。首先采用灰色关联度分析算法得出影响消费者购房需求和偏好的关键因子,然后采用Apriori算法对关键因子和目标因子之间进行关联规则挖掘。以某市问卷调查的消费者信息记录进行建模,结果表明该关联分析方法具有较高的挖掘效率并且研究结果具有合理性和准确性。

Association analysis is an important data mining techniques. In this paper, combined the characteristics of the real estate industry ,the association analysis method is applied to the study of consumer purchase behavior. The traditional association rule mining algo- dthm-Apriori algorithm has large calculation,the low efficiency of mining,resulting in a large number of irrelevant association rules in practical applications. In order to reduce computation, improve the efficiency of mining and find valuable association rules, the combina- tion method of gray relational analysis algorithm and Apriori algorithm is presented. First of all, gray relational analysis algorithm to draw the key factors affecting consumer purchase requirements and preferences, and then use the Apriori algorithm for mining association rules between the key factor and the target factor. The modeling results show that the association analysis method has a high efficiency of mining and the findings has the reasonableness and accuracy of consumer information records of a city survey.