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Usually, people will search on the Internet for movie that they want to watch. However, it is tedious to find and choose movie that matched with their preferences due to a lot of information on the Internet. Therefore, most of the movie portals are adopting recommendation engine to filter and disp...

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Bibliographic Details
Main Authors: Khatun, Jannatara, Loh, Teck Chwen, Foo, Hooi Ling, Akit, Henny, Khan, Kabirul I.
Format: Article
Language:English
Published: Frontiers Media 2020
Online Access:http://psasir.upm.edu.my/id/eprint/89138/1/CYC.pdf
http://psasir.upm.edu.my/id/eprint/89138/
https://www.frontiersin.org/articles/10.3389/fvets.2020.00619/full
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Summary:Usually, people will search on the Internet for movie that they want to watch. However, it is tedious to find and choose movie that matched with their preferences due to a lot of information on the Internet. Therefore, most of the movie portals are adopting recommendation engine to filter and display user’s personalized content. In this paper, MyRecMovie is presented to recommend movies by using graph-powered recommendation engine. MyRecMovie adopts content based (CB) and collaborative filtering (CF) approaches with then further enhance the recommendations with graph-powered recommendation engine to provide movie recommendations to the user.