《计算机应用研究》|Application Research of Computers

考虑价格的跨种类模糊序列模式挖掘算法

Cross-category fuzzy sequential pattern mining algorithm with consideration of price

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作者 高增,郭均鹏
机构 天津大学 管理与经济学部,天津 300072
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文章编号 1001-3695(2018)01-0039-04
DOI 10.3969/j.issn.1001-3695.2018.01.007
摘要 消费者对不同种类的产品具有不同的价格偏好,而传统的序列模式挖掘算法仅考虑序列中不同项目的出现顺序,使得挖掘到的序列模式没有包含产品价格以及种类等重要信息。为了克服传统算法的这一缺陷,在序列模式中体现更多的用户行为信息,基于模糊集理论,提出了一种在产品种类维度上进行的跨种类模糊价格序列模式挖掘算法。实验结果表明,与传统序列模式挖掘算法相比,该算法可以有效解决序列数据的稀疏性问题,能够挖掘得到更多个性化的序列模式。
关键词 序列模式;产品价格;价格偏好;模糊集;跨种类
基金项目 国家自然科学基金资助项目(71271147,71671121)
本文URL http://www.arocmag.com/article/01-2018-01-007.html
英文标题 Cross-category fuzzy sequential pattern mining algorithm with consideration of price
作者英文名 Gao Zeng, Guo Junpeng
机构英文名 Dept.ofManagement&Economics,TianjinUniversity,Tianjin300072,China
英文摘要 Consumers held different price preferences for products of various categories, but the traditional sequential pattern mining algorithms only considered the appearance orders of different items within a sequence. Therefore, the obtained sequential patterns didn’t contain the important information, such as price and category attributes. In order to overcome the defects of traditional algorithms and embody more user behavior information in the sequential patterns, this paper proposed a cross-cate-gory fuzzy price sequential pattern mining algorithm. The experimental results indicate that, compared with traditional sequential pattern mining algorithms, the proposed algorithm can effectively solve the data sparsity problem and mine more persona-lized sequential patterns.
英文关键词 sequential pattern; product price; price preference; fuzzy set; cross-category
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收稿日期 2016/8/22
修回日期 2016/10/17
页码 39-42,47
中图分类号 TP391
文献标志码 A