id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-027078-i3a5jwck	Jiang, Bo	Social Recommendation in Heterogeneous Evolving Relation Network	2020-05-26		.txt	text/plain	3985	271	52	In this paper, we propose a novel social recommendation model based on evolving relation network, named SoERec. The learned evolving relation network is a heterogeneous information network, where the strength of relation between users is a sum of the influence of all historical events. -We propose a novel social recommendation model by jointly embedding representations of fine-grained relations from historical events based on heterogeneous evolving network. -We conduct several analysis experiments with two real-world social network datasets, the experimental results demonstrate our proposed model outperforms state-of-the art comparison methods. Various methods of social recommendation have been proposed from different perspectives in recent years including user-item rating matrix [15] , network structure [11] , trust relationship [5, 10, 18, 27] , individual and friends' preferences [6, 12] , social information [25] and combinations of different features [19, 26] . In particular, we leverage the LINE model to learn users' embedded representations of the evolving relation network the firstorder proximity and the second-order proximity.	./cache/cord-027078-i3a5jwck.txt	./txt/cord-027078-i3a5jwck.txt