Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection.
Contribuinte(s) |
Department of Computer Science Advanced Reasoning Group |
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Data(s) |
21/01/2008
21/01/2008
2006
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Resumo |
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. 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. Non peer reviewed |
Formato |
10 |
Identificador |
Jensen , R & Shen , Q 2006 , ' Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection. ' pp. 147-156 . PURE: 74193 PURE UUID: 3176f7b0-ae47-45f6-bc95-a6fcc65c6d9a dspace: 2160/442 |
Idioma(s) |
eng |
Tipo |
/dk/atira/pure/researchoutput/researchoutputtypes/contributiontoconference/paper |
Relação | |
Direitos |