189 / 2016-12-29 02:29:09
An Improved Approach for Movie Recommendation System
Draft Accepted
Shreya Agrawal / SVITS
Pooja Jain / SVITS
In this hustling world, entertainment is a necessity for each one of us to refresh our mood and energy. Entertainment regains our confidence for work and we can work more enthusiastically. For revitalizing ourselves, we can listen to our preferred music or can watch movies of our choice. For watching favorable movies online we can utilize movie recommendation systems, which are more reliable, since searching of preferred movies will require more and more time which one cannot afford to waste. In this paper, to improve the quality of a movie recommendation system, a Hybrid approach by combining content based filtering and collaborative filtering, using Support Vector Machine as a classifier and genetic algorithm is presented in the proposed methodology and comparative results have been shown which depicts that the proposed approach shows an improvement in the accuracy, quality and scalability of the movie recommendation system than the pure approaches in three different datasets. Hybrid approach helps to get the advantages from both the approaches as well as tries to eliminate the drawbacks of both methods.
Important Date
  • Conference Date

    Mar 22

    2017

    to

    Mar 24

    2017

  • Feb 15 2017

    Draft paper submission deadline

  • Feb 20 2017

    Draft Paper Acceptance Notification

  • Feb 22 2017

    Final Paper Deadline

  • Mar 24 2017

    Registration deadline