基于改进数据过滤算法的异构数据库优化挖掘技术  

Heterogeneous Database Optimization Mining Technology Based on the Improved Data Filtering Algorithm

作　　者：杨海霞[1] 

机构地区：[1]山西大学商务学院,太原030031

出　　处：《科技通报》2013年第6期125-127,共3页Bulletin of Science and Technology

基　　金：软科学研究方法与工具包集成应用研究--以山西省软科学研究项目为例(2011041025-02)

摘　　要：针对数据库中数据关联较弱,干扰数据复杂度过大,减弱了数据库挖掘效率的问题,提出一种基于改进数据过滤算法的异构数据库优化挖掘技术。通过在原始数据中加入改进的过滤算法,保证数据多样性的前提下能够快速进入小规模频繁集进行挖掘,克服传统方法挖掘能力差等缺陷。仿真结果表明,加入改进过滤算法后的挖掘算法加快了求解数据库多连接查询优化问题的速度,提高了查询优化效率,得到较满意的查询优化结果。According to the database data association is weak,the interference data excessive complexity.Weaken the database mining efficiency problem.This paper puts forward a data filter algorithm based on improved the isomerism database optimization mining technology.In the original data by adding improved filter algorithm,to ensure that the data under the premise of diversity can be quickly into the small frequent sets mining,overcome traditional method mining capacity of some shortcomings.The simulation results show that the improved filter algorithm to speed up the mining algorithm for solving database connection query optimization problem of speed,but also improves the query optimization efficiency,get satisfactory query optimization results.

关 键 词：数据库 数据挖掘 过滤算法 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]