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  • 标题:Preparing Annotated Data on Covid -19 by Employing Naïve Bayes
  • 本地全文:下载
  • 作者:Dipankar Das ; Akash Ghosh ; AdityaR Rayala
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2021
  • 卷号:11
  • 期号:12
  • 语种:English
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:The on-going pandemic has opened the pandora’s box of the plethora of hidden problems which the society has been hiding for years. But the positive side to the present scenario is the opening up of opportunities to solve these problems on the global stage. One such area which was being flooded with all kinds of different emotions, and reaction from the people all over the world, is twitter, which is a micro blogging platform. Coronavirus related hash tags have been trending all over for many days unlikeany other event in the past. Our experiment mainly deals with the collection, tagging and classification of these tweets based on the different keywords that they may belong to, using the Naive Bayes algorithm atthe core.
  • 关键词:Covid-19;Naïve Bayes;Clustering
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