Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection.

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dc.contributor.author Jensen, Richard
dc.contributor.author Shen, Qiang
dc.date.accessioned 2008-01-21T12:45:06Z
dc.date.available 2008-01-21T12:45:06Z
dc.date.issued 2006
dc.identifier.citation Jensen , R & Shen , Q 2006 , ' Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection. ' pp. 147-156 . en
dc.identifier.other PURE: 74193
dc.identifier.other dspace: 2160/442
dc.identifier.uri http://hdl.handle.net/2160/442
dc.description R. Jensen and Q. Shen, 'Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection,' Proceedings of the Fifth International Conference on Rough Sets and Current Trends in Computing (RSCTC 2006), LNAI 4259, pp. 147-156, 2006. en
dc.description.abstract Due to the explosive growth of electronically stored information, automatic methods must be developed to aid users in maintaining and using this abundance of information effectively. In particular, the sheer volume of redundancy present must be dealt with, leaving only the information-rich data to be processed. This paper presents an approach, based on an integrated use of fuzzy-rough sets and Ant Colony Optimization (ACO), to greatly reduce this data redundancy. The work is applied to the problem of webpage categorization, considerably reducing dimensionality with minimal loss of information. en
dc.format.extent 10 en
dc.language.iso eng
dc.relation.ispartof en
dc.title Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection. en
dc.type Text en
dc.type.publicationtype Conference paper en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Non peer reviewed en


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