id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_h3zthufefjdy5fufaftvouocdu	Ismail Ahmed Al-Qasem Al-Hadi	Latent based temporal optimization approach for improving the performance of collaborative filtering	2020	25	.pdf	application/pdf	10037	1212	64	prediction of products depends on the latent features of users in a rating matrix. of CF recommender systems by combining the latent factors, short-term preferences, Compared to other temporal approaches (e.g., the short-term based 2017a) addresses the drift issue not solved by previous short-term based approaches. • An LTO approach that learns the drift in the users' interests through an improved prediction accuracy in the CF technique by learning accurate latent effects of the temporal It utilizes to find similar users or items and calculate predicted rating scores according The long temporal-based factorization approach (Al-Hadi et al., 2018b) learns The LTO approach addresses both long and short temporal preferences by using temporal-based factorization) are used to predict missing rating scores in the rating matrix temporal vectors in improving the prediction accuracy of the CF using the LTO approach. of the long temporal-based factorization approach (Al-Hadi et al., 2018b) is to solve the	./cache/work_h3zthufefjdy5fufaftvouocdu.pdf	./txt/work_h3zthufefjdy5fufaftvouocdu.txt