吉林大学学报(信息科学版) ›› 2022, Vol. 40 ›› Issue (4): 652-656.

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基于数据挖掘地域性强关联规则数据提取

陈 刚   

  1. 广州华商学院 数据科学学院, 广州 511300
  • 收稿日期:2021-11-25 出版日期:2022-08-16 发布日期:2022-08-17
  • 作者简介:陈刚(1973— ), 男, 长沙人, 广州华商学院讲师, 主要从事数据挖掘数据分析和知识图谱研究, ( Tel)86-13824483568 (E-mail)chen38744882@163.com。
  • 基金资助:
    教育部高等教育司 2020 年产学合作协同育人基金资助项目(202002159002); 广东省哲学社会科学规划基金资助项目
    (GD17XGL19); 广东省普通高校创新团队基金资助项目(2020WCXTD008)

Data Extraction Method of Regional Strong Association Rules Based on Data Mining

CHEN Gang   

  1. School of Data Science, Guangzhou Huashang College, Guangzhou 511300, China
  • Received:2021-11-25 Online:2022-08-16 Published:2022-08-17

摘要: 针对数据提取方法无法进行海量挖掘, 且挖掘结果不准确, 挖掘时间较长的问题, 提出一种基于数据挖掘算法的地域性强关联规则数据提取方法。 结合地域性强关联规则数据管理系统, 采集用户需求信息, 检索特征关联性, 收集地域特征。 利用数据关联度, 分析地域检索中地域特征间的关联, 计算相似标签信息参数,并对支持度和置信度实施计算, 从地域性强关联规则数据库中挖掘关联规则。 利用 Kulczynski 量度和不平衡率实施相关性分析和过滤, 最终获取到具有实际意义的强关联规则。 实验结果表明, 该方法挖掘效率较高, 且具有广泛的应用价值。

关键词: 数据关联度; , 地域性强关联规则数据; , 数据提取; , 强关联规则

Abstract: Aiming at the problem that the data extraction method can not carry out massive mining, the mining results are inaccurate and the mining time is long, a regional strong association rule data extraction method based on data mining algorithm is proposed. Combined with the data management system of strong regional association rules, user demand information is collected, feature relevance is retrieved, drama features are obtained. The data relevance is used to analyze the association between drama features in drama retrieval, calculate similar label information parameters, calculate the support and confidence, and mine association rules from the database of strong regional association rules. Kulczynski measure and imbalance rate is used to implement correlation
analysis and filtering, and finally the strong association rules are obtained with practical significance. The experimental results show that this method has high mining efficiency and wide application value.

Key words: data association degree; , regional and strong association rule data; , data fetch; , strong association rules

中图分类号: 

  • TP312