Empowering Quality of Recommendations by Integrating Matrix Factorization Approaches With Louvain Community Detection

Empowering Quality of Recommendations by Integrating Matrix Factorization Approaches With Louvain Community Detection

Recommendation systems play an important role in creating personalized content for consumers, improving their overall experiences across several applications. Providing the user with accurate recommendations based on their interests is the recommender system’s primary goal. Collaborative...

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Bibliographic Details
Main Authors: Srilatha Tokala, Murali Krishna Enduri, T. Jaya Lakshmi, Ashu Abdul, Jenhui Chen
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Recommendation system
collaborative filtering
community detection
matrix factorization
Online Access:https://ieeexplore.ieee.org/document/10743182/
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