概率关联规则在图书流通量挖掘中的应用

Application of Book Circulation Mining Using Probability Association Rule

本文提出了一种概率关联规则算法,通过使用概率的方法估算任意数据项集在事务数据库中出现的概率来求候选频繁项集,并给出了相关算法描述及其算法实现。将本算法与Apriori算法产生的候选项集大小和扫描数据库次数进行了比较,它大大的减少了扫描数据库的次数。最后本文讨论了如何将概率关联规则算法应用于大学图书馆图书流通量挖掘中,以达到图书馆藏结构优化的目的。

A probability association rules algorithm of Apriori is presented in this paper. The paper estimates the probability of dataset items appearing in the database using the probability computing, moreover provides the description and the realization of the relative algorithm. The paper compares the probability association rules with Apriori algorithm. The priority of the improved algorithm is that it reduces the times of scanning DB. Finally, the paper discusses how to apply the probability association rules algorithm into the book circulation of college library in order to optimize the structure of library collections.