Segregation of Live News Articles Based on Location Using Machine Learning

Authors

  • Heneil Tayade  Department of Computer Engineering, Datta Meghe College of Engineering, Navi Mumbai, Maharashtra, India
  • Chaitanya Shetty  Department of Computer Engineering, Datta Meghe College of Engineering, Navi Mumbai, Maharashtra, India
  • Ratika Jankar  Department of Computer Engineering, Datta Meghe College of Engineering, Navi Mumbai, Maharashtra, India
  • Dr. Amol Pande   Department of Computer Engineering, Datta Meghe College of Engineering, Navi Mumbai, Maharashtra, India

DOI:

https://doi.org/10.32628/CSEIT206380

Keywords:

Machine Learning, Random Forest, SVM, Naive Bayes, News classification.

Abstract

As we all know web contains an enormous amount of data which is gigantic and it is changing continuously for each minute and we also know during this hectic lifestyle it's very difficult to stay track of each news and article that's occurring. So, people are mostly focused on the news which goes into their nearby environment. During this paper, we consider displaying the news directing on the nearby cities and also displaying the required news articles supported by a few important cities. Here, we've a web crawler which is used to withdraw the content from the HTML pages of the articles. Random forest, Naïve Bayes and SVM classifiers are used to compute the precision and their accuracy is being calculated. Machine Learning is the well- known technique used for this type of news classification and displaying of the news articles

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-06-30

Issue

Volume 6, Issue 3, May-June-2020

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Heneil Tayade, Chaitanya Shetty, Ratika Jankar, Dr. Amol Pande , " Segregation of Live News Articles Based on Location Using Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 3, pp.505-512, May-June-2020. Available at doi : https://doi.org/10.32628/CSEIT206380