document: Eliminating noisy information in Web pages for data mining A commercial Web page typically contains many information blocks . Apart from the main content blocks , it usually has such blocks as navigation panels , copyright and privacy notices , and advertisements ( for business purposes and for easy user access ) . We call these blocks that are not the main content blocks of the page the noisy blocks . We show that the information contained in these noisy blocks can seriously harm Web data mining . Eliminating these noises is thus of great importance . In this paper , we propose a noise elimination technique based on the following observation : In a given Web site , noisy blocks usually share some common contents and presentation styles , while the main content blocks of the pages are often diverse in their actual contents and\/or presentation styles . Based on this observation , we propose a tree structure , called Style Tree , to capture the common presentation styles and the actual contents of the pages in a given Web site . By sampling the pages of the site , a Style Tree can be built for the site , which we call the Site Style Tree ( SST ) . We then introduce an information based measure to determine which parts of the SST represent noises and which parts represent the main contents of the site . The SST is employed to detect and eliminate noises in any Web page of the site by mapping this page to the SST . The proposed technique is evaluated with two data mining tasks , Web page clustering and classification . Experimental results show that our noise elimination technique is able to improve the mining results significantly .
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