电信科学 ›› 2012, Vol. 28 ›› Issue (1): 117-121.doi: 10.3969/j.issn.1000-0801.2012.01.022

• 研究与开发 • 上一篇    下一篇

基于语言值模糊关系的关联规则挖掘算法

方美玉,郑小林,陈德人   

  1. 1．浙江大学计算机科学与技术学院 杭州310027;2．浙江外国语学院信息学院 杭州310012
  • 发布日期:2017-02-07
  • 基金资助:
    国家自然科学基金资助项目;国家科技支撑计划基金资助项目;浙江省自然科学基金资助项目;浙江省自然科学基金资助项目

Association Rules Mining Algorithm Based on Fuzzy Relation of Linguistic Value

Meiyu Fang,Xiaolin Zheng,Deren Chen   

  1. 1.Computer Science and Technology of Zhejiang University,Hangzhou 310027,China;2.School of Information,Zhejiang International Studies University,Hangzhou 310012,China
  • Published:2017-02-07

在线阅读

1

PDF下载

556

被引次数

13

摘要：

针对模糊关联规则挖掘时隶属函数的确定困难以及区间划分边界过硬等问题，提出了模糊关系关联规则挖掘算法，确定了关系等级数目和相邻等级相似度，将语言表达式（事务的属性值）根据模糊运算规则映射到标签集的各个等级上得到等级权值。在这些权值的基础上定义了模糊关系支持度和置信度，阐述了算法的详细步骤，最后给出了算法在服务信任领域挖掘关联规则的应用过程。

关键词: 语言值, 模糊关系, 关联规则, 服务信任领域

Abstract:

For the difficult determining of the membership function and the hard border of interval division when the fuzzy association rules are mining,association rules mining algorithm based on fuzzy relation is proposed.After the relation grade numbers and the similarity of neighbor grades are determined,the linguistic expressions （the properties of transactions）are mapped to each grade of the label set and then get the grade ratings as the weights.Based on these weights,the fuzzy relation support and confidence are defined.The detailed steps of the algorithm are elaborated in this paper.At the end of this article the application of this proposed algorithm about mining association rules in service trust area is described.

Key words: linguistic value, fuzzy relation, association rule, service trust area

No Suggested Reading articles found!