%0 Journal Article
%T Web Pages Information Retrieval Based on Keywords Cluster and Node Instance<br>基于关键词聚类和节点距离的网页信息抽取
%A DENG Jian-Shuang
%A ZHENG Qi-Lun
%A PENG Hong
%A LIN Xu-Dong
%A <br>邓健爽
%A 郑启伦
%A 彭宏
%A 林旭东
%J 计算机科学
%D 2007
%I 
%X Many Web information retrieval methods are related to special Web sites, for example, the method based on extracting rules and the one based on training page samples. These methods can do well in a Web site but fail in the others without adding new rules or inputting new training pages manually. Furthermore, if the template of the Web site is changed, it has to redesign the extracting rules or re-inputting the training pages. It is hard to be maintained and used to extract information from large number of different Web sites. In the paper, there is a new method which can extract the useful information from the different sites automatically based on the keywords of a certain topic and the distance of the nodes. Experimental evaluation on a large of Web pages from different Web sites indicates that this method correctly and automatically extracts the information ignoring which Web sites the pages come from. This method has been applied to the system of intelligent searching and mining of electronic business successfully.
%K Cluster
%K Information retrieval
%K Machine learning
%K Instance of node<br>聚类
%K 信息抽取
%K 机器学习
%K 节点距离
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=1E8759907DE654785AC99B2944611D38&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=E158A972A605785F&sid=527AEE9F3446633A&eid=CEC789B3C68C3BB3&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=11