Ranking and Quick Access of Information Hybrid Content Based and Hmm in Health Care Social Media

Authors

  • S. Sudhakarilango  Department of Computer Science, Anna University, Sri Krishna College of Engineering of Technology, Tamil Nadu, India
  • V. Hemalatha  Department of Computer Science, Anna University, Sri Krishna College of Engineering of Technology, Tamil Nadu, India

Keywords:

Hadoop, (HMM) Hidden markov model, social media, Big Data

Abstract

Internet has become a media of communication. Web 2.0 increases its’ impact and make it as social media where people can share all the information. Using this people is forming a group, forum for discussion etc. This discussion group becomes a vital source of information. This forum discussion is available for all fields like medical, computer science, engineering and technology. Since millions and millions of people is using net as forum information evolved over a net is huge and decision making based on these huge information is also complex task. Hadoop framework provides a solution for this big data analysis. As a research work, forum of health care community is selected. In the forum, patients can post quires, share therapy followed, prescription prescribed. To make this forum more beneficial for beneficiary, the comments posted are ranked. For accurate ranking and quick access of information Content Based Mining along with hidden markov model (HMM) is used.

References

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Published

2017-12-31

Issue

Section

Research Articles

How to Cite

[1]
S. Sudhakarilango, V. Hemalatha, " Ranking and Quick Access of Information Hybrid Content Based and Hmm in Health Care Social Media, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 2, pp.477-481, March-April-2016.