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Designing Distributed Recommender Systems using Map Reduce Paradigm -A Study

P.S. Chakraborty1

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-01 , Page no. 289-292, Jan-2019

Online published on Jan 20, 2019

Copyright © P.S. Chakraborty . 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: P.S. Chakraborty, “Designing Distributed Recommender Systems using Map Reduce Paradigm -A Study,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.01, pp.289-292, 2019.

MLA Style Citation: P.S. Chakraborty "Designing Distributed Recommender Systems using Map Reduce Paradigm -A Study." International Journal of Computer Sciences and Engineering 07.01 (2019): 289-292.

APA Style Citation: P.S. Chakraborty, (2019). Designing Distributed Recommender Systems using Map Reduce Paradigm -A Study. International Journal of Computer Sciences and Engineering, 07(01), 289-292.

BibTex Style Citation:
@article{Chakraborty_2019,
author = {P.S. Chakraborty},
title = {Designing Distributed Recommender Systems using Map Reduce Paradigm -A Study},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {07},
Issue = {01},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {289-292},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=634},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=634
TI - Designing Distributed Recommender Systems using Map Reduce Paradigm -A Study
T2 - International Journal of Computer Sciences and Engineering
AU - P.S. Chakraborty
PY - 2019
DA - 2019/01/20
PB - IJCSE, Indore, INDIA
SP - 289-292
IS - 01
VL - 07
SN - 2347-2693
ER -

           

Abstract

Nowadays Recommender Systems play an important role in E-Commerce domain. It helps customers to buy the right product or service by generating recommendations. In this paper, a detailed survey has been made regarding the works proposed by different researchers for designing recommender systems in distributed environment. A general framework for designing user-based and item-based recommender systems using map-reduce paradigm has been provide thereafter.

Key-Words / Index Term

Recommender system, Collaborative filtering, Bigdata, Map-reduce,P2P network

References

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