id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_hmonw5eaebaelbnpnt6dmeypoy	Douglas Véras	CD-CARS: Cross-Domain Context-Aware Recommender Systems	2019	241	.pdf	application/pdf	69799	7443	63	Figure 13 – The cross-domain post-filtering recommendation is made over the aggregated user-rating matrices and then post-filtered according to contextual (std) by varying the user overlap level for all contextual value combinations from the temporal and location dimensions (source domain: (std) by varying the user overlap level for all contextual value combinations from the temporal and location dimensions (source domain: Book, (std) by varying the user overlap level for all contextual value combinations from the temporal and location dimensions (source domain: Book, (std) by varying the user overlap level for all contextual value combinations from the temporal and location dimensions (source domain: Music, The context-aware approach uses different contextual information (e.g., location, time, mood, etc.) to improve the accuracy of recommendations (ADOMAVICIUS; Although many cross-domain RS have used contextual information in an adhoc way as part of their knowledge-based approaches (see Section 2.4.2) (BLANCOFERNÁNDEZ et al., 2011)(MOE; AUNG, 2014b)(KAMINSKAS et al., 2014), to the	./cache/work_hmonw5eaebaelbnpnt6dmeypoy.pdf	./txt/work_hmonw5eaebaelbnpnt6dmeypoy.txt