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A Three Way Hybrid Movie Recommendation Syste

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Karan Soni, Rinky Goyal, Bhagyashree Vadera, Siddhi More
10.5120/ijca2017913026

Karan Soni, Rinky Goyal, Bhagyashree Vadera and Siddhi More. A Three Way Hybrid Movie Recommendation Syste. International Journal of Computer Applications 160(9):29-32, February 2017. BibTeX

@article{10.5120/ijca2017913026,
	author = {Karan Soni and Rinky Goyal and Bhagyashree Vadera and Siddhi More},
	title = {A Three Way Hybrid Movie Recommendation Syste},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2017},
	volume = {160},
	number = {9},
	month = {Feb},
	year = {2017},
	issn = {0975-8887},
	pages = {29-32},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume160/number9/27103-2017913026},
	doi = {10.5120/ijca2017913026},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Recommendation Systems or Engines are found in many applications. These systems or Engines offer the user or service subscriber with a list of suggestions or recommendations that they might choose based on the user’s already known preferences. In this paper, the focus is on combining a content-based algorithm, a User-based collaborative filtering algorithm, and review based text mining algorithm in the application of a tailored movie recommendation system. Here movies are recommended based on ratings explicitly provided by the user and according to the ratings and reviews of movies provided by other users as well. Here the propose is to generate polarity ratings to Characteristics of a movie instead of generating a wholesome rating to an available text based review to gain better insights about preferences of users, thus refining Movie recommendation systems further.

References

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Keywords

SVM classification, user based collaborative filtering, Content based filtering