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  • 标题:A NOVEL K-NN CLASSIFICATION APPROACH USING TOPIC MODELLING IN AMINER DATASET
  • 本地全文:下载
  • 作者:Dr.G.Ayyappan ; Dr.C.Nalini ; Dr.A.Kumaravel
  • 期刊名称:Indian Journal of Computer Science and Engineering
  • 印刷版ISSN:2231-3850
  • 电子版ISSN:0976-5166
  • 出版年度:2019
  • 卷号:10
  • 期号:2
  • 页码:40-44
  • 出版社:Engg Journals Publications
  • 摘要:Social network is a structure of human relations and association. It is made up of a organizedsocial actors in a network form. Information has varied number of forms and various purposes forcommunication. Journals serve as major source of primary information.The topics were divided intocategories, such as Algorithm, Data mining, Database, Artificial Intelligence, Clinical, Medical Imaging,Image Processing, Biomedical Informatics, Image Processing, and Telemedicine, which happens to be alittle exercise around the topic modeling. The problem of extracting from the huge dataset for authorarticle relationship with appropriate classifier with best accuracy was considered by carrying out theexperiment in this chapter.
  • 关键词:LinearNNSearch; BallTree; Filtered-NeigbhourSearch; Euclidean; Manhattan; and Chebyshev.
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