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Collaborative Filtering for Movie Recommendation using RapidMiner

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Arpita Jain, Santosh K. Vishwakarma
10.5120/ijca2017914771

Arpita Jain and Santosh K Vishwakarma. Collaborative Filtering for Movie Recommendation using RapidMiner. International Journal of Computer Applications 169(6):29-33, July 2017. BibTeX

@article{10.5120/ijca2017914771,
	author = {Arpita Jain and Santosh K. Vishwakarma},
	title = {Collaborative Filtering for Movie Recommendation using RapidMiner},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {169},
	number = {6},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {29-33},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume169/number6/27991-2017914771},
	doi = {10.5120/ijca2017914771},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Recommender System is a special type of information filtering system that provides a prediction which helps the user to evaluate items from a huge collection that the user is likely to find interesting or useful. Recommender System is used to produce meaningful suggestions about new items for particular consumers. These recommendations facilitate the users to make decisions in multiple contexts, such as what items to buy, what online news to read or what music to listen to. Recommender Systems have become important in information and decision overloaded in the world. Recommender Systems helped their founders to increase profits. This paper, presents a brief overview of collaborative filtering based movie recommender system and their implementation using rapid miner.

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Keywords

Recommender System, collaborative filtering, utility matrix, rapidminer operators.