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• W2092582006 abstract "This paper explores website link structure considering websites as interconnected graphs and analyzing their features as a social network. Two networks have been extracted for representing websites: a domain network containing subdomains or external domains linked through the website and a page network containing webpages browsed from the root domain. Factor analysis provides the statistical methodology to adequately extract the main website profiles in terms of their internal structure. However, due to the large number of indicators, the task of selecting a representative subset of indicators becomes unaffordable. A genetic search of an optimum subset of indicators is proposed in this paper, selecting a multi-objective fitness function based on factor analysis results. The optimum solution provides a coherent and relevant categorization of website profiles, and highlights the possibilities of genetic algorithms as a tool for discovering new knowledge in the field of web mining." @default.
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• W2092582006 date "2012-10-01" @default.
• W2092582006 modified "2023-10-03" @default.
• W2092582006 title "An evolutionary factor analysis computation for mining website structures" @default.
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• W2092582006 doi "https://doi.org/10.1016/j.eswa.2012.04.011" @default.
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