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  • 标题:A Genetic approach to Classify Text Documents by Utilizing Term features
  • 本地全文:下载
  • 作者:Shabana Bee ; Sumit Gupta
  • 期刊名称:International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
  • 印刷版ISSN:2278-1323
  • 出版年度:2016
  • 卷号:5
  • 期号:12
  • 页码:2762-2768
  • 出版社:Shri Pannalal Research Institute of Technolgy
  • 摘要:As the text document are increasing day by day with thegrowing digital world. Researchers are working in this field from lastfew decades. In this paper a genetic algorithm is proposed on classifythe text document in efficient manner. At present teachers learningalgorithm is utilize for the classification which is known as geneticapproach. Proposed classification approach classifies the data on thebasis two phase learning where best probable solution is consider asthe teacher phase while in second phase individual solution will learnfrom each other. In each phase new probable solution having highfitness value is preserve while low fitness value probable solutionwas discard. Experiment is done real as well as artificial dataset.Proposed work is compare with fire fly genetic approach and resultsshows that proposed work is better as compare to previous work ondifferent evaluation parameters.
  • 关键词:Document; genetic algorithum; feature extraction; text;categorization; clustering
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