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An Exhaustive Study on Context based Recommender Systems

by Shubham Mastkar, Urjita Thakar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 11
Year of Publication: 2024
Authors: Shubham Mastkar, Urjita Thakar
10.5120/ijca2024923463

Shubham Mastkar, Urjita Thakar . An Exhaustive Study on Context based Recommender Systems. International Journal of Computer Applications. 186, 11 ( Mar 2024), 17-21. DOI=10.5120/ijca2024923463

@article{ 10.5120/ijca2024923463,
author = { Shubham Mastkar, Urjita Thakar },
title = { An Exhaustive Study on Context based Recommender Systems },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2024 },
volume = { 186 },
number = { 11 },
month = { Mar },
year = { 2024 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number11/an-exhaustive-study-on-context-based-recommender-systems/ },
doi = { 10.5120/ijca2024923463 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-03-23T00:18:05.451949+05:30
%A Shubham Mastkar
%A Urjita Thakar
%T An Exhaustive Study on Context based Recommender Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 11
%P 17-21
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Enormous amount of digital information has made it increasingly challenging to identify the relevant information for users. Recommender systems were introduced to solve this problem by providing personalized recommendations to users. Context-based recommender systems are recent which uses contextual information to provide more personalized recommendations. In this paper, an exhaustive study of context-based recommender systems has been presented. The key concepts and various approaches used in context-based recommender systems have been discussed. Various application areas have also been presented.

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Index Terms

Computer Science
Information Sciences

Keywords

Context-Based Recommender Systems Personalized Recommendations Contextual Information Approaches in Recommender Systems Recommender System Application Areas

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