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  • 标题:Document Clustering with Evolutionary Systems through Straight-Line Programs “slp”
  • 本地全文:下载
  • 作者:José Luis Castillo Sequera ; José Raúl Fernández del Castillo Diez ; León Gonzalez Sotos
  • 期刊名称:Journal of Intelligent Learning Systems and Applications
  • 印刷版ISSN:2150-8402
  • 电子版ISSN:2150-8410
  • 出版年度:2012
  • 卷号:4
  • 期号:4
  • 页码:303-318
  • DOI:10.4236/jilsa.2012.44032
  • 出版社:Scientific Research Publishing
  • 摘要:In this paper, we show a clustering method supported on evolutionary algorithms with the paradigm of linear genetic programming. “The Straight-Line Programs (slp)”, which uses a data structure which will be useful to represent collections of documents. This data structure can be seen as a linear representation of programs, as well as representations in the form of graphs. It has been used as a theoretical model in Computer Algebra, and our purpose is to reuse it in a completely different context. In this case, we apply it to the field of grouping library collections through evolutionary algorithms. We show its efficiency with experimental data we got from traditional library collections.
  • 关键词:Clustering; Genetic Algorithm; Data Mining; Straight Line Programs
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