关键词: 交叉营销, 分类, 关联规则, 频繁闭项集

Abstract: In order to guide commercial decisions for cross marketing, a new classification algorithm named CHC based on frequent closed itemsets and imprecise reasoning was proposed. The H-C algorithm for mining frequent closed itemsets based on hyperlinked data structure, H-Struct, was improved. The header table of H-Struct was adjusted by inserting the class label to prune the search space; the local relative support and maximum support were used to exclude meaningless patterns; the maximum length of patterns mined was applied to improve the usability of rules. The reasoning algorithm of EMYCIN was extended to handle the rules whose right is negative. The algorithm improved above traditional classification algorithm's limitations in deriving only class label. Furthermore, this algorithm obtained a value referring to the confidence of the classification result to facilitate and simplify the process of evaluating multiple cross marketing plans. The experimental results show that the enhanced algorithm is efficient in run time and classification precision.

Key words: cross marketing, classification, association rule, frequent closed itemsets