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  • 标题:Monitoring Partial Update of Web Pages by Interactive Classification Learning
  • 本地全文:下载
  • 作者:Seiji YAMADA ; Yuki Nakai
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2002
  • 卷号:17
  • 期号:5
  • 页码:614-621
  • DOI:10.1527/tjsai.17.614
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:This paper describes an automatic monitoring system that constantly checks partial update in Web pages and notifies them to a user. While one of the most important advantages of the WWW is update of Web pages, we need to constantly check them out and this task takes much cognitive load. Thus applications to automatically check update of Web pages have been developed, however they can not deal with partial update like update in a particular cell in a table in a Web page. Hence we developed a automatic monitoring system that checks such partial update. A user can give a system regions in which he/she wants to know the update in a Web page as training examples, and it is able to learn rules to identify the partial update by classification learning. By this learning, a user do not need to directly describe the rules. We implemented our system and some executed examples were presented.
  • 关键词:the WWW ; monitoring of partial update ; classification learning ; interactive system
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