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ITCC
2005
IEEE

Elimination of Redundant Information for Web Data Mining

14 years 5 months ago
Elimination of Redundant Information for Web Data Mining
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 ted 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.
Shakirah Mohd Taib, Soon-ja Yeom, Byeong Ho Kang
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where ITCC
Authors Shakirah Mohd Taib, Soon-ja Yeom, Byeong Ho Kang
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