Machine Learning Text Categorization In OSN To Filter Unwanted Messages

Abstract

One fundamental issue in today’s Online Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now, OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning-based soft classifier automatically labeling messages in support of content-based filtering.

Authors and Affiliations

Kota Prudhvee Raj| M.Tech, Department of Computer Science and Engineering, Sir C R Reddy College of Engineering, Eluru, West Godavari District Andhra Pradesh, India – 534007 Prudhvi9889@gmail.com, Kotaru Anil Chowdary| Associate Professor, Department of Computer Science and Engineering, Sir C R Reddy College of Engineering, Eluru, West Godavari District Andhra Pradesh, India – 534007 anilchow@gmail.com

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  • EP ID EP16635
  • DOI -
  • Views 325
  • Downloads 11

How To Cite

Kota Prudhvee Raj, Kotaru Anil Chowdary (2015). Machine Learning Text Categorization In OSN To Filter Unwanted Messages. International Journal of Science Engineering and Advance Technology, 3(11), 951-954. https://europub.co.uk/articles/-A-16635