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PC Configuration and Component Recommendation System

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 11
Year of Publication: 2021
Authors:
Someshkumar Mishra, Shreyas Bane, Rahul Pandit, Neelam Phadnis
10.5120/ijca2021921411

Someshkumar Mishra, Shreyas Bane, Rahul Pandit and Neelam Phadnis. PC Configuration and Component Recommendation System. International Journal of Computer Applications 183(11):5-8, June 2021. BibTeX

@article{10.5120/ijca2021921411,
	author = {Someshkumar Mishra and Shreyas Bane and Rahul Pandit and Neelam Phadnis},
	title = {PC Configuration and Component Recommendation System},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2021},
	volume = {183},
	number = {11},
	month = {Jun},
	year = {2021},
	issn = {0975-8887},
	pages = {5-8},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume183/number11/31969-2021921411},
	doi = {10.5120/ijca2021921411},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Recommendation Systems are created to recommend appropriate products to users from a collection of products with various complex attributes. Personal Computers have an assortment of components that vary incompatibility with each other. Due to the large number of possible configurations and parameters to consider, it is difficult for laymen to try making their configurations. It is also difficult to compare which components are similar to each other. This paper presents a recommendation system for these components using collaborative filtering.

References

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Keywords

PC Configuration, Recommendation, Machine Learning, KNN, Collaborative Filtering, Computer Hardware.