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Leveraging Modified Social Group Optimization for Enhanced E-Commerce Recommendation Systems

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Title Leveraging Modified Social Group Optimization for Enhanced E-Commerce Recommendation Systems
 
Creator Sahu, Sai Shaktimayee
Satapathy, Suresh Chandra
 
Subject Collaborative filtering
e-Commerce
SGO
Evolutionary optimization
Recommendation system
 
Description 274-281
Intelligent recommendation systems have gained significant popularity in recent times due to their ability to ease item or
service selection for users and enhance profit-making opportunities for businesses. E-commerce recommender systems are
in high demand across online platforms. There is a pressing need for continuous innovation to improve the performance of
these e-commerce recommendation systems in terms of accuracy in suggesting preferences. However, many existing
recommendation systems are not able to perform well when there is a data sparsity or incomplete data. To address above
challenges, this study introduces a novel approach that combines collaborative filtering with Modified Social Group
Optimization (MSGO), a type of evolutionary optimization methods. The main objective is to improve the precision of the
recommendation system specifically for movie recommendations. The collaborative filtering technique is leveraged to
analyse user-item interactions and find patterns to predict user preferences. To evaluate the proposed system, a simulation is
conducted using movie recommendation data. The results demonstrate that the integration of MSGO into the collaborative
filtering framework yields improved performance compared to the original SGO algorithm. These findings provide
promising evidence for the effectiveness of MSGO in enhancing the accuracy of movie recommendations within the ecommerce
context.
 
Date 2024-03-06T11:38:47Z
2024-03-06T11:38:47Z
2024-03
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/63543
https://doi.org/10.56042/jsir.v83i3.4358
 
Language en
 
Publisher NIScPR-CSIR, India
 
Source JSIR Vol.83(3) [March 2024]