Temporal integration based factorization to improve prediction accuracy of collaborative filtering

Temporal integration based factorization to improve prediction accuracy of collaborative filtering

A recommender system provides users with personalized suggestions for items based on the user’s behaviour history. These systems often use the collaborative filtering (CF) for analysing the users’ preferences for items in the rating matrix. The rating matrix typically contains a high percentage of...

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Bibliographic Details
Main Author:	Al-Qasem, Al-Hadi Ismail Ahmed
Format:	Thesis
Language:	English
Published:	2016
Subjects:	Recommender systems (Information filtering)
Online Access:	http://psasir.upm.edu.my/id/eprint/69372/1/FSKTM%202016%2040%20IR.pdf

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