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Title: Movie Recommendation System Using Sentiment Analysis from Microblogging Data
Authors: Kumar S.
De K.
Pratim Roy, Partha
Published in: IEEE Transactions on Computational Social Systems
Abstract: Recommendation systems (RSs) have garnered immense interest for applications in e-commerce and digital media. Traditional approaches in RSs include such as collaborative filtering (CF) and content-based filtering (CBF) through these approaches that have certain limitations, such as the necessity of prior user history and habits for performing the task of recommendation. To minimize the effect of such limitation, this article proposes a hybrid RS for the movies that leverage the best of concepts used from CF and CBF along with sentiment analysis of tweets from microblogging sites. The purpose to use movie tweets is to understand the current trends, public sentiment, and user response of the movie. Experiments conducted on the public database have yielded promising results. © 2014 IEEE.
Citation: IEEE Transactions on Computational Social Systems, 7(4): 915-923
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Collaborative filtering
content-based filtering
recommendation system (RS)
sentiment analysis
ISSN: 2329924X
Author Scopus IDs: 57197068495
Author Affiliations: Kumar, S., Department of Computer Science and Engineering, IIT Roorkee, Roorkee, India
De, K., Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
Roy, P.P., Department of Computer Science and Engineering, IIT Roorkee, Roorkee, India
Corresponding Author: Kumar, S.; Department of Computer Science and Engineering, India; email:
Appears in Collections:Journal Publications [CS]

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