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  • 标题:Deep Web Search in Data Mining for Data Extraction
  • 本地全文:下载
  • 作者:Nripendra Narayan Das ; Dimpy Gambhir
  • 期刊名称:International Journal of Research in Management, Science & Technology
  • 印刷版ISSN:2321-3264
  • 出版年度:2014
  • 卷号:2
  • 期号:3
  • 出版社:Prannath Parnami Institute of Management & Technology, Hisar
  • 摘要:WWW stands for World Wide Web, and it is an advanced information retrieval system. As years passed World Wide Web became weighed down with information and it became hard to retrieve data according to the need. The Web mining extracts useful information from the web pages. Web mining techniques seek to extract knowledge from Web data, including web documents, hyperlinks between documents, and usage logs of web sites. Web usage mining mines knowledge from diverse websites. Extracting appropriate data from deep web pages is an exigent dilemma due to the overflow of data in to the web. Web servers generates a huge amount of information on web users browsing activities. These are called click stream or web access log data. The click stream data can be enriched with information about the content of visited pages.The aim of this paper is to obtain all the data behind a form by multiple submissions of the form filled out in all possible ways by using agent, but efficiency concerns lead us to consider alternatives. We can estimate the amount of remaining data after a small number of submissions maximize the coverage of the data.
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