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  • 标题:Text Mining on Twitter Data Using Visualizing Technique R
  • 本地全文:下载
  • 作者:Aalia Bano Qureshi ; Dr. Tripti Arjariya ; Dr. Mohit Gangwar
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2017
  • 卷号:6
  • 期号:3
  • 页码:4751
  • DOI:10.15680/IJIRSET.2017.0603265
  • 出版社:S&S Publications
  • 摘要:‘BIG DATA’ is getting a more importance in different industries over the last year or two, on the basisof large amount of data is generated by different industries every day. The term Big Data is applied to large data sets sothe traditional databases was unable to store thar large data sets like a traditional way and unable to process such largedatasets. It has huge potential to transform business and power in several ways. Here the challenge is not only storingthe data, but also accessing and analyzing the required data in specified amount of time. One of the most powerfulaspects of using R is that you can download free packages for so many tools and types of analysis. Text analysis is stillsomewhat in its infancy, but is very promising. It is estimated that as much as 80% of the world’s data is unstructured,while most types of analysis only work with structured data. In this paper, we will explore the potential of R packagesto analyze unstructured text and pre-processed the text and after that we can visualize the result.
  • 关键词:Big data; R; Unstructure data; text mining; visualization
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