Optimizing Parallel Collaborative Filtering Approaches for Improving Recommendation Systems Performance

Optimizing Parallel Collaborative Filtering Approaches for Improving Recommendation Systems Performance

Recommender systems are one of the fields of information filtering systems that have attracted great research interest during the past several decades and have been utilized in a large variety of applications, from commercial e-shops to social networks and product review sites. Since the applicabili...

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Bibliographic Details
Main Authors:	Christos Sardianos, Grigorios Ballas Papadatos, Iraklis Varlamis
Format:	Article
Language:	English
Published:	MDPI AG 2019-04-01
Series:	Information
Subjects:	recommender systems collaborative filtering scalability graph partitioning distributed systems parallel execution social networks
Online Access:	https://www.mdpi.com/2078-2489/10/5/155

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