User Based Efficient Video Recommendatıon System

  • J. Albert Mayan
  • R. Aroul Canesaane
  • J. Jabez
  • M. D. Kamalesh
  • G. Rama Mohan Reddy
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)


The quick increment in the online data content has made it extremely troublesome for individuals to discover data that is pertinent to their requirements and interests. Proposal framework is an intense apparatus that gives a potential answer for this test by offering a mechanized component to search out applicable and new data. Individuals depend on client surveys on the web when they require data about item, motion picture, video, news, eatery, and so on. In any case, fundamental issue is giving suggestion to client shape huge information environment. Huge information is a rising innovation, as the name recommends is about taking care of huge measure of information, technique and preparing the information inside middle of the road passed time. An enormous information is gathered and handled to settle on some choice furthermore used to portray any sort of information which might be organized, semi-organized, unstructured and if the information develops. In this work our primary commitment is to prescribe online recordings to client in view of client intrigue. In past framework, recordings were positioned in view of the viewer of that video yet in our proposed framework recordings are positioned and prescribed to client in view of remarks, check and likes. Here client can give remarks just in the event that he/she has watched that specific video, generally clients are not qualified to give remarks on that video. By the assistance of this element we rank recordings in remarks and likes based. The upgrade of our proposition is the opinion grouping of client remarks, with two conceivable marks: negative (neg) and positive (pos). The given technique is utilized to enhance the versatility and effectiveness, if information develops.


Videos User comments Ranking algorithm Recommend system 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • J. Albert Mayan
    • 1
  • R. Aroul Canesaane
    • 2
  • J. Jabez
    • 2
  • M. D. Kamalesh
    • 1
  • G. Rama Mohan Reddy
    • 3
  1. 1.School of ComputingSathyabama Institute of Science and TechnologyChennaiIndia
  2. 2.School of Computing/ECESathyabama Institute of Science and TechnologyChennaiIndia
  3. 3.Department of Computer Science and EngineeringSathyabama Institute of Science and TechnologyChennaiIndia

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