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  • 标题:Categorize Online news Using Various Classification Techniques
  • 本地全文:下载
  • 作者:Neeru Sharma ; Paramjit Kaur
  • 期刊名称:International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
  • 印刷版ISSN:2278-1323
  • 出版年度:2015
  • 卷号:4
  • 期号:2
  • 页码:337-340
  • 出版社:Shri Pannalal Research Institute of Technolgy
  • 摘要:Classification is a data mining technique used to predict group membership for data instances. It is often referred as "supervised learning". It has a predefined set of groups or models based on that we predict value [2]. In this age of information, news is now easily accessible, as content providers and content locators such as online news services have sprouted on the World Wide Web. Since the emergence of WWW, it is essential to handle a very large amount of electronic data of which the majority is in the form of text. This scenario can be effectively handled by various Data Mining techniques. This paper proposes an intelligent system for classify the inner structures of the online news based on Neural Network (NN) and Support Vector Machine (SVM).For the current scenario, the work has just been done to identify the outer clusters of the system but no work till now has been done for inner cluster of the datasets. In this proposed work, we would be creating inners clusters for each and every field of the proposed system like Sports, Entertainment and Financial. In this work we would be creating clusters for Sports, Entertainment and Financial also so that we can go on for better accuracy.
  • 关键词:Text Classification; Support Vector Machines ; (SVM); Neural Network; Online News
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