An Innovative Technique based on Topical Modeling for Personalized Movie Searched Engine

  • Authors

    • Lokendra Birla
    • Rohit Dhangar
    • Anand Kumar
    • Yogesh Singh
    2018-12-13
    https://doi.org/10.14419/ijet.v7i4.39.23818
  • Personalized movie search engine(PMSE), Latent Dirichlet Allocation (LDA), Dual Personalized Ranking function (D-PR).

  • Abstract

    A large an amount of information is becoming available and this information is valuable source of intelligence but it is very difficult to extract or mine useful information for making decision. To overcome this type of problem, there are information filtering systems, such as  the personalized movie searched engine (PMSE). This PMSE identifying interest of person on his/her preferences. This PMSE utilized user’s reviews to create a personalized profile of user. First of preprocess the reviews then use Latent Dirichlet Allocation (LDA) for generating topic from user reviews. Finally, Dual Personalized Ranking function (D-PR) [1] will rank movies when the user enters a query. Experiment result shows that our system is able to give personalized movie search results to the user.


     

  • References

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  • How to Cite

    Birla, L., Dhangar, R., Kumar, A., & Singh, Y. (2018). An Innovative Technique based on Topical Modeling for Personalized Movie Searched Engine. International Journal of Engineering & Technology, 7(4.39), 105-108. https://doi.org/10.14419/ijet.v7i4.39.23818

    Received date: 2018-12-12

    Accepted date: 2018-12-12

    Published date: 2018-12-13