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J4 ›› 2011, Vol. 46 ›› Issue (5): 67-70.

• SEWM 2011 会议 • 上一篇    下一篇

基于Apriori算法的Deep Web网页关系挖掘研究

李贵,韩子扬,郑新录,李征宇   

  1. 沈阳建筑大学信息与控制工程学院,  辽宁 沈阳 110168
  • 收稿日期:2010-12-06 发布日期:2011-05-25
  • 作者简介:李贵(1964- ),男,教授,博士, 研究方向为软件工程,分布对象技术,Web数据挖掘与信息集成. Email:Phenixhans@163.com

Study on Deep Web pages mining based on Apriori algorithm

LI Gui, HAN Zi-yang, ZHENG Xin-lu, LI Zheng-yu   

  1. Information & Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, Liaoning, China
  • Received:2010-12-06 Published:2011-05-25

摘要:

利用Apriori算法对Deep Web网站中最大频繁关联关系网页进行识别,并对非最大频繁项网页进行剪枝,再遍历Deep Web网站网页,从而获取所有最大频繁关联关系网页。对某房地产Deep Web网站的实验结果验证了该算法的可行性和有效性。

关键词: Deep Web;Apriori算法;剪枝算法;特征码

Abstract:

The max frequent association pages in Deep Web sites are recognized by using Apriori algorithm, and the non-max frequent association pages are  pruned.Then, all the max frequent association pages are obtained by website traversing. Experimental results of some real estate Deep Web data extraction prove that the algorithm is feasible and valid.

Key words:  Deep Web; Apriori algorithm; pruning algorithm; feature code

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