Using Knowledge Base for Event-Driven Scheduling of Web Monitoring Systems

  • Authors:

  • Yang Sok Kim;Sung Won Kang;Byeong Ho Kang;Paul Compton

  • Affiliations:

  • School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia 2001 and School of Computing and Information Systems, University of Tasmania, Hobart, Australia 700 ...;School of Computing and Information Systems, University of Tasmania, Hobart, Australia 7001;School of Computing and Information Systems, University of Tasmania, Hobart, Australia 7001;School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia 2001

  • Venue:
  • EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
  • Year:
  • 2009

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Abstract

Web monitoring systems report any changes to their target web pages by revisiting them frequently. As they operate under significant resource constraints, it is essential to minimize revisits while ensuring minimal delay and maximum coverage. Various statistical scheduling methods have been proposed to resolve this problem; however, they are static and cannot easily cope with events in the real world. This paper proposes a new scheduling method that manages unpredictable events. An MCRDR (Multiple Classification Ripple-Down Rules) document classification knowledge base was reused to detect events and to initiate a prompt web monitoring process independent of a static monitoring schedule. Our experiment demonstrates that the approach improves monitoring efficiency significantly.