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“MovieReco” Hybrid movie recommendation framework based on user reviews

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dc.contributor.author Wijeratne, Maleesha Dilnath
dc.date.accessioned 2020-05-05T17:30:08Z
dc.date.available 2020-05-05T17:30:08Z
dc.date.issued 2019
dc.identifier.citation Wijeratne, Maleesha Dilnath (2019) “MovieReco” Hybrid movie recommendation framework based on user reviews. BSc. Dissertation Informatics Institute of Technology. en_US
dc.identifier.other 2015355
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/297
dc.description.abstract It is both challenging and an overwhelming task to select a movie to watch, out of many movies, which has been already released and that are being releasing. Even though the scenarios are such, people tend check others opinions in terms of reviews to make the choices a bit easier and get a prior understanding about a movie. As a solution to make the peoples choices much easier when it comes to looking for movies, the system proposed to develop a movie recommendation framework which analyses user reviews and based on features and sentiments underlying on reviews to make recommendation of similar movies. The system makes use of Natural Language Processing and sentiment analysis techniques to make more accurate recommendations. en_US
dc.subject Natural Language Processing en_US
dc.subject Sentiment Analysis en_US
dc.title “MovieReco” Hybrid movie recommendation framework based on user reviews en_US
dc.type Thesis en_US


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