基于模糊关联规则的分布式通信网络数据库分类挖掘方法
Classified Mining Method of Distributed Communication Network Database Based on Fuzzy Association Rules
越琳1
作者信息
- 1. 郑州财经学院商学院,河南郑州 450000
- 折叠
摘要
当处理海量数据库时,传统的方法在对分布式通信网络数据库进行分类挖掘时往往难以准确确定数据库之间的关联度,因此导致分类挖掘的数量偏低.为了解决这一问题,提出了一种基于模糊关联规则的分布式通信网络数据库分类挖掘方法.该方法利用模糊关联规则来选择特征、构建分类函数、计算数据类别的相异度,并设计分类挖掘规则,从而最终实现对数据库的分类挖掘.实验结果表明,该方法在处理分布式通信网络数据库时具有较高的分类效率,对数据库管理具有帮助.
Abstract
When dealing with massive databases,traditional methods often find it difficult to ac-curately determine the correlation between databases when classifying and mining distributed communication network databases,resulting in a low number of classification mining.To ad-dress this issue,a distributed communication network database classification mining method based on fuzzy association rules is proposed.This method utilizes fuzzy association rules to select features,construct classification functions,calculate the dissimilarity of data categories,and de-sign classification mining rules,ultimately achieving classification mining of databases.The ex-perimental results show that this method has high classification efficiency when dealing with distributed communication network databases and is helpful for database management.
关键词
模糊关联规则/选择特征/分布式通信网络数据库/分类挖掘方法Key words
Fuzzy association rules/Select features/Distributed communication network data-base/Classification mining methods引用本文复制引用
出版年
2024
NETL
NSTL
万方数据