Library Open Repository

Dynamic Web Content Filtering Based on User's Knowledge

Downloads

Downloads per month over past year

Churcharoenkrung, N and Kim, YS and Kang, BH (2005) Dynamic Web Content Filtering Based on User's Knowledge. In: International Conference on Information Technology, 4-6 April 2005, Las Vegas, USA.

[img]
Preview
PDF
PID51343.pdf | Download (200kB)
Available under University of Tasmania Standard License.

Abstract

This paper focuses on the development of a maintainable information filtering system. The simple and efficient solution to this problem is to block the Web sites by URL, including IP address. However, it is not efficient for unknown Web sites and it is difficult to obtain complete block list. Content based filtering is suggested to overcome this problem as an additional strategy of URL filtering. The manual rule based method is widely applied in current content filtering systems, but they overlook the knowledge acquisition bottleneck problems. To solve this problem, we employed the Multiple Classification Ripple-Down Rules (MCRDR) knowledge acquisition method, which allows the domain expert to maintain the knowledge base without the help of knowledge engineers. Throughout this study, we will prove the MCRDR based information filtering system can easily prevent unknown Web information from being delivered and easily maintain the knowledge base for the filtering system.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Keywords: Ripple Down Rules RDR MCRDR information filtering Web filter
Publisher: IEEE
Page Range: pp. 184-188
Date Deposited: 18 May 2005
Last Modified: 18 Nov 2014 03:10
URI: http://eprints.utas.edu.au/id/eprint/176
Item Statistics: View statistics for this item

Repository Staff Only (login required)

Item Control Page Item Control Page