Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.eswa.2012.04.011 | Expert Syst. Appl. |
Keywords | Field | DocType |
mining website structure,social network,website profile,external domain,main website profile,genetic algorithm,page network,domain network,factor analysis,website link structure,factor analysis result,evolutionary factor analysis computation,evolutionary computation,genetic algorithms,link analysis | Data mining,Categorization,Web mining,Social network,Web page,Link analysis,Computer science,Evolutionary computation,Fitness function,Artificial intelligence,Genetic algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
39 | 14 | 0957-4174 |
Citations | PageRank | References |
2 | 0.36 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. R. Martínez-Torres | 1 | 132 | 9.83 |
| Sergio L. Toral Marín | 2 | 167 | 18.81 |
| B. Palacios | 3 | 2 | 0.70 |
| Federico Barrero | 4 | 161 | 13.96 |