面向电子商务的万维网知识发现数据聚类的粗糙集方法

H. K. Tripathy, B. Tripathy
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引用次数: 8

摘要

数据挖掘和/或知识发现是当今电子商务的一个非常重要的部分。万维网已经成为现实,几乎任何人都可以访问互联网的最大的在线信息。本文提出了一个电子商务框架,并利用知识发现技术实现个性化电子商务,增加交叉销售,改善客户关系管理。由于Web的巨大规模和用户查询的低精度,目前的Web搜索引擎返回的结果可以达到数百甚至数千个数据。因此,找到正确的信息即使不是不可能,也是很困难的。试图解决这个问题的一种方法是使用聚类技术将相似的数据分组在一起,以便以更紧凑的形式表示结果,并允许浏览结果集。本文介绍了一种数据聚类技术,重点介绍了它在Web搜索结果中的应用。提出了一种基于粗糙集的Web数据聚类算法,并讨论了该算法的具体实现。
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A Rough Set Approach for Clustering the Data Using Knowledge Discovery in World Wide Web for E-Business
Data mining and/or knowledge discovery is a very important part of today's e-business. The World Wide Web has become in reality, the largest online information available practically to anyone with access to Internet. An e-business framework is proposed in the paper, as well as the knowledge discovery technique to personalize e-business, increase cross selling, and improve the customer relationship management. Due to the enormous size of the Web and low precision of user queries, results returned from present Web search engines can reach hundreds or even thousands data. Therefore, finding the right information can be difficult if not impossible. One approach that tries to solve this problem is by using clustering techniques for grouping similar data together in order to facilitate presentation of results in more compact form and enable browsing of the results set. In this paper, a data clustering techniques is presented with emphasis on application to Web search results. An algorithm for clustering Web data based on Rough Set is presented and its practical implementation is discussed.
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