UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 8
August-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2308665


Registration ID:
524047

Page Number

g602-g608

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Title

Exploring the landscape of the recommendation system: methodology, scope, application, techniques

Abstract

The study "Exploring the Landscape of the Recommendation System: Scope, Methodology, Application, Learning Paradigms" carries out an in-depth analysis of the many aspects of recommendation systems. The wide range of methodologies, programs, and learning paradigms related to recommendation systems are examined in this work. The research thoroughly investigates the methods used to develop recommendation systems, such as content-based, collaborative-based hybrid, demographic, and knowledge-based, and highlights how effective they are in resolving a variety of problems. The article also investigates the wide range of application domains, highlighting the valuable contributions of recommendation systems to improving user experiences in e-commerce, content delivery, and personalized services, among other areas. Additionally, the research explores the fundamental learning principles that underpin recommendation systems, providing insights into the numerous methods used for prediction and customization. In essence, this research paper offers a comprehensive overview of the landscape of recommendation system. This study essentially provides a thorough summary of the current state of recommendation systems. It is a useful tool for academics, professionals, and other interested parties who want to fully understand this crucial field.

Key Words

Recommendation system, exploration, scope, methodology, application, learning paradigms, content delivery, machine learning model, Deep Learning, hybrid approaches, Content-based recommender system, Demographic recommendation system, Generative Recommendation System

Cite This Article

"Exploring the landscape of the recommendation system: methodology, scope, application, techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.g602-g608, August-2023, Available :http://www.jetir.org/papers/JETIR2308665.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Exploring the landscape of the recommendation system: methodology, scope, application, techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppg602-g608, August-2023, Available at : http://www.jetir.org/papers/JETIR2308665.pdf

Publication Details

Published Paper ID: JETIR2308665
Registration ID: 524047
Published In: Volume 10 | Issue 8 | Year August-2023
DOI (Digital Object Identifier):
Page No: g602-g608
Country: Pune, Maharashtra, India .
Area: Other
ISSN Number: 2349-5162
Publisher: IJ Publication


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