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中文摘要：
针对Apriori算法扫描数据库的I/O代价和候选项集数目较多等问题,提出一种基于矩阵的强关联规则生成算法。该算法通过将事务数据库转换为0-1矩阵后对项集按照支持度计数非递减顺序排列,从而减少了候选项集的产生,同时实现置信度的高效计算。通过对实例和大数据量数据库的分析表明,该方法是有效的。
英文摘要：
Apriori,the classic association rule mining algorithm,has the problems of higher I/O cost and more candidate itemsets in the process of finding out the frequent itemsets.Here,proposed a new algorithm generating strong association rules based on matrix.The new algorithm could only scan the database for one time to convert the transactions into matrix which was composed by 0 and 1,and could be reordered by item support count non-descending order to reduce the number of candidate itemsets,meanwhile,the efficiency of association rule confidence computing could be enhanced too.The analysis results of exa-mples and large database show that the proposed method is effective.
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