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Monitoring web resources discovery by reusing classification knowledge
Any automated client pull systems, such as web monitoring systems, Web services, or RSS systems, require resources that publish relevant information. These resources may be discovered manually, but this is not ideal. Public search engines may be used to find these resources by submitting appropriate queries. In the previous re- search, we proposed a search query formulation method that reuses MCRDR (Multiple Classification Ripple-Down Rules) classification knowledge bases. However, all search results may not relevant web resources, because they may not resources, but web pages linked from the candidate resources. Therefore, it is necessary to develop methods that locate candidate monitoring web resources from search results. This pa- per summarizes heuristics that were obtained user study, which will be used in this automated resource location process.
History
Publication title
Proceedings Social Computing and Behavioural ModelingEditors
H Lui, JJ Salerno, MJ YoungPagination
ejISBN
978-1-4419-0055-5Department/School
School of Information and Communication TechnologyPublisher
SpringerPlace of publication
New York, USAEvent title
Social Computing and Behavioural ModelingEvent Venue
Phoenix, ArizonaDate of Event (Start Date)
2009-03-31Date of Event (End Date)
2009-04-01Rights statement
The original publication is available at http://www.springerlink.comRepository Status
- Restricted