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Elimination of Redundant Information for Web Data Mining
Taib, SM and Yeom, SJ and Kang, BH (2005) Elimination of Redundant Information for Web Data Mining. In: International Conference on Information Technology, 4-6 April 2005, Las Vegas, USA.
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These days, billions of Web pages are created with HTML or other markup languages. They only have a few uniform structures and contain various authoring styles compared to traditional text-based documents. However, users usually focus on a particular section of the page that presents the most relevant information to their interest. Therefore, Web documents classification needs to group and filter the pages based on their contents and relevant information. Many researches on Web mining report on mining Web structure and extracting information from web contents. However, they have focused on detecting tables that convey specific data, not the tables that are used as a mechanism for structuring the layout of Web pages. Case modeling of tables can be constructed based on structure abstraction. Furthermore, Ripple Down Rules (RDR) is used to implement knowledge organization and construction, because it supports a simple rule maintenance based on case and local validation.
|Item Type:||Conference or Workshop Item (Paper)|
|Keywords:||Web Monitoring, Web information management, Ripple Down Rules, RDR, MCRDR|
|Page Range:||pp. 200-205|
|Date Deposited:||18 May 2005|
|Last Modified:||18 Nov 2014 03:10|
|Item Statistics:||View statistics for this item|
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