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Reseach Article

PC Configuration and Component Recommendation System

by Someshkumar Mishra, Shreyas Bane, Rahul Pandit, Neelam Phadnis
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, Neelam Phadnis . PC Configuration and Component Recommendation System. International Journal of Computer Applications. 183, 11 ( Jun 2021), 5-8. DOI=10.5120/ijca2021921411

@article{ 10.5120/ijca2021921411,
author = { Someshkumar Mishra, Shreyas Bane, Rahul Pandit, Neelam Phadnis },
title = { PC Configuration and Component Recommendation System },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2021 },
volume = { 183 },
number = { 11 },
month = { Jun },
year = { 2021 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number11/31969-2021921411/ },
doi = { 10.5120/ijca2021921411 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:16:29.895962+05:30
%A Someshkumar Mishra
%A Shreyas Bane
%A Rahul Pandit
%A Neelam Phadnis
%T PC Configuration and Component Recommendation System
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 11
%P 5-8
%D 2021
%I Foundation of Computer Science (FCS), NY, 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
  1. Nawrocka, A. Kot and M. Nawrocki, "Application of machine learning in recommendation systems," 2018 19th International Carpathian Control Conference (ICCC), Szilvasvarad, 2018, pp. 328-331, doi: 10.1109/CarpathianCC.2018.8399650.
  2. Zisopoulos, Charilaos&Karagiannidis, Savvas&Demirtsoglou, Georgios &Antaris, Stefanos. (2008). Content-Based Recommendation Systems.
  3. Wen, Zheng. (2012). Recommendation System Based on Collaborative Filtering.
  4. M. Gupta, A. Thakkar, Aashish, V. Gupta and D. P. S. Rathore, "Movie Recommender System Using Collaborative Filtering," 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India, 2020, pp. 415-420, doi: 10.1109/ICESC48915.2020.915
Index Terms

Computer Science
Information Sciences

Keywords

PC Configuration Recommendation Machine Learning KNN Collaborative Filtering Computer Hardware.