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Building a Movie Recommendation System using SVD algorithm

Asoke Nath1 , Adityam Ghosh2 , Arion Mitra3

Section:Survey Paper, Product Type: Journal Paper
Volume-6 , Issue-11 , Page no. 727-729, Nov-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i11.727729

Online published on Nov 30, 2018

Copyright © Asoke Nath, Adityam Ghosh, Arion Mitra . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Asoke Nath, Adityam Ghosh, Arion Mitra, “Building a Movie Recommendation System using SVD algorithm,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.727-729, 2018.

MLA Style Citation: Asoke Nath, Adityam Ghosh, Arion Mitra "Building a Movie Recommendation System using SVD algorithm." International Journal of Computer Sciences and Engineering 6.11 (2018): 727-729.

APA Style Citation: Asoke Nath, Adityam Ghosh, Arion Mitra, (2018). Building a Movie Recommendation System using SVD algorithm. International Journal of Computer Sciences and Engineering, 6(11), 727-729.

BibTex Style Citation:
@article{Nath_2018,
author = {Asoke Nath, Adityam Ghosh, Arion Mitra},
title = {Building a Movie Recommendation System using SVD algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2018},
volume = {6},
Issue = {11},
month = {11},
year = {2018},
issn = {2347-2693},
pages = {727-729},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3234},
doi = {https://doi.org/10.26438/ijcse/v6i11.727729}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i11.727729}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3234
TI - Building a Movie Recommendation System using SVD algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - Asoke Nath, Adityam Ghosh, Arion Mitra
PY - 2018
DA - 2018/11/30
PB - IJCSE, Indore, INDIA
SP - 727-729
IS - 11
VL - 6
SN - 2347-2693
ER -

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Abstract

Recommendation System predicts or recommends a set of products or items based upon the preference of the user. Recommender systems are utilized in variety of areas including movies, music, news, books search queries in general. This paper focuses on the design and development of a movie recommendation system using the SVD (Singular Value Decomposition) algorithm where we see that how sparse data are in real life situation and thereby predefined strategies such as collaborative or content-based filtering cannot be applied to these data for better results. Our objective is to reduce the sparsity of the data using dimensionality reduction by the SVD algorithm and hence recommend a list of movies based on the given input parameters.

Key-Words / Index Term

Recommendation System, SVD Decomposition, Netflix, Dimensionality reduction

References

[1] F. Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4, Article 19 (December 2015), 19 pages. DOI=
[2] B.M. Sarwar, et, "Application of Dimensionality Reduction in Recommender System—A Case Study," Proc. KDD Workshop on Web Mining for e-Commerce: Challenges and Opportunities (WebKDD), ACM Press, 2000.
[4] Bobadilla, J., Ortega, F., Hernando, A., Gutierrez, A.: Recommender systems survey. Knowledge-Based Systems 46(0), 109–132 (2013)
[5]To view full code visit the following link:
https://github.com/lucifermorningstar1305/machine_learning/blob/master/Codelogicx/Codelogicx/RecommenderSystemFinal. ipynb