University Of Tasmania
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Personalized Web Document Classification using MCRDR

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conference contribution
posted on 2023-05-26, 07:20 authored by Park, SS, Kim, YS, Kang, BH
This paper focuses on real world Web document classification problem. Real world Web documents classification has different problems compare to experimental based classification. Web documents have been continually increased and their themes also have been continually changed. Furthermore, domain users' knowledge is not fixed apart from classification environments. They learn from classification experience, broaden their knowledge, and tend to reclassify pre-classified Web documents according to newly obtained knowledge to fit various contexts. To handle these kinds of problems, we use Multiple Classification Ripple-Down Rules (MCRDR) knowledge acquisition method. The MCRDR based document classification enables domain users to elicit their domain knowledge incrementally and revise their knowledge base (KB), and consequently reclassify preclassified documents according to context changes. Our experiment results show MCRDR document classifier performs these tasks successfully in the real world.





School of Computing, Unviersity of Tasmania

Publication status

  • Published

Event title

Pacific Knowledge Acquisition Workshop 2004

Event Venue

Auckland, New Zealand

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Repository Status

  • Open

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