Rules revisited: web page classification
CI '07 Proceedings of the Third IASTED International Conference on Computational Intelligence
Semantic Space models for classification of consumer webpages on metadata attributes
Journal of Biomedical Informatics
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Today's search engines retrieve tens of thousands of web pages in response to fairly simple query articulations. These pages are retrieved on the basis of the query terms occurring in the web pages and the popularity of the web pages as per the link structure of the web. However, these search engines do not take into account the broader information need of the user, such as the task in which the user is involved. This research investigates the automatic categorization of web pages using Principal Component Analysis. The research focuses on user tasks that involve searching for web pages containing health information, education information or shopping information. Initial results are encouraging with recall and precision values slightly in excess of 80%.