Abstract
Nowadays, we are living in an age recommendation, but the proper recommendation needs more accurate and relevant datas as their inputs. Rating databases like MovieLence or Netflix have long been popular and being widely used in recommendation system areas for research in past decades. But nowadays, they become irrelevant due to lack of new and relevant datas. Nowadays, social media like Facebook and Twitter become the most popular for researchers due to availability of large amount of new and relevant datas. In this paper, we have built a recommendation engine by analyzing rating datasets collected from Twitter to recommend movies to specific user using R.
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Acknowledgements
We are thankful to the faculty members of School of Computer Engineering Department of KIIT University, Bhubaneswar, for their cooperation and suggestions.
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Das, D., Chidananda, H.T., Sahoo, L. (2018). Personalized Movie Recommendation System Using Twitter Data. In: Pattnaik, P., Rautaray, S., Das, H., Nayak, J. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-7871-2_33
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DOI: https://doi.org/10.1007/978-981-10-7871-2_33
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