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Monitoring web resources discovery by reusing classification knowledge


Kang, BH and Kim, YS, Monitoring web resources discovery by reusing classification knowledge, Proceedings Social Computing and Behavioural Modeling, 31 March -1 April 2009, Phoenix, Arizona EJ ISBN 978-1-4419-0055-5 (2009) [Refereed Conference Paper]

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DOI: doi:10.1007/978-1-4419-0056-2


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.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Artificial intelligence not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Kang, BH (Professor Byeong Kang)
UTAS Author:Kim, YS (Dr Yang Kim)
ID Code:62419
Year Published:2009
Deposited By:Information and Communication Technology
Deposited On:2010-03-12
Last Modified:2015-02-13

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