基于WEKA平台的Web事务聚类算法的研究  

Study to web transactions clustering algorithm on WEKA

作　　者：孟晓明[1] 陈慧萍[1] 张涛[1] 

机构地区：[1]河海大学计算机信息工程学院,江苏常州213022

出　　处：《计算机工程与设计》2009年第6期1332-1334,1338,共4页Computer Engineering and Design

摘　　要：Web上的数据规模大、动态性强,而通常发现的知识或规则很可能是不精确的、不完备的,为了克服以上困难,将粗糙集概念引入到Web挖掘中,进行Web事务聚类。介绍了将粗糙近似算法嵌入到WEKA平台的过程,充分利用了开源WEKA中的类和可视化功能,扩充了WEKA系统的聚类算法,并对嵌入的算法进行了分析、测试。粗糙近似算法方法能够实现从Web访问日志中聚类Web事务,并且该算法对分类属性的数据具有很高的准确率。The web data has a large scale and dynamic speciality and the discovered knowledge or rules are likely to be imprecise or incomplete generally. To the difficulties, rough sets is introduced into the web mining to cluster web transactions. The process of embedding the rough approximation algorithm into the WEKA platform in which the classes and visualization functions of open source WEKA is fully utilized. The rough approximation algorithms extended the clustering algorithm in the WEKA system. The embedded algorithm is analyzed and tested. The rough algorithm can cluster web transactions from web access logs and it has a higher veracity for the nominal data.

关 键 词：粗糙集 WEB挖掘 粗糙近似 事务聚类 相似上近似 WEKA平台 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]