BPF plus plus : A Unified Factorization model for predicting retweet behaviors

doi:10.1016/j.ins.2019.12.017

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	BPF plus plus : A Unified Factorization model for predicting retweet behaviors
	Wang, Shaoqing 1; Li, Cuipin 2; Wang, Zheng 3; Chen, Hong 2; Zheng, Kai 4
刊名	INFORMATION SCIENCES
	2020-04-01
卷号	515 页码:218-232
关键词	Collaborative filtering Bayesian Poisson factorization Probabilistic model Retweet behaviors Social network
ISSN号	0020-0255
DOI	10.1016/j.ins.2019.12.017
英文摘要	Recently, the prediction of retweet behaviors has attracted significant attention, as it can facilitate with a number of tasks, such as popular tweet prediction, personalized recommendation and business intelligence. However, in existing studies, two main problems exists in the prediction of retweet behaviors. (1) The relationship between users is extremely simple when social influences are used for prediction. (2) An effective framework that unifies the effects of both heterogeneous social relations of users and multidimensional similarities of tweets does not exist. Therefore, we propose a unified factorization model that incorporates social influence and tweet similarity into a traditional Bayesian Poisson factorization (BPF) model, named BPF++. Specifically, we utilize a variety of social influence and tweet similarity jointly to improve performance. Furthermore, we integrate trust strengths between users and degrees of similarity between tweets to the framework. We adopt an efficient coordinate ascent algorithm to learn the parameters of the BPF++ model. Extensive experiments are conducted to evaluate the performance of our model on the Sina Weibo dataset. Results demonstrate improvements of 113.64% and 116.28% in the NDCG@3 and precision@3 scores, respectively, compared with BPF. (C) 2019 Elsevier Inc. All rights reserved.
资助项目	National Key Research Develop Plan[2018YFB1004401] ; NSFC[61772537] ; NSFC[61772536] ; NSFC[61702522] ; NSFC[61532021] ; NSFC[61902222]
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000513293200013
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/14504]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Cuipin
作者单位	1.Shandong Univ Technol, Sch Comp Sci & Technol, Zibo, Shandong, Peoples R China 2.Renmin Univ China, Key Lab Data Engn & Knowledge Engn MOE, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing, Peoples R China 4.Univ Elect Sci & Technol China, Sichuan, Peoples R China
推荐引用方式 GB/T 7714	Wang, Shaoqing,Li, Cuipin,Wang, Zheng,et al. BPF plus plus : A Unified Factorization model for predicting retweet behaviors[J]. INFORMATION SCIENCES,2020,515:218-232.
APA	Wang, Shaoqing,Li, Cuipin,Wang, Zheng,Chen, Hong,&Zheng, Kai.(2020).BPF plus plus : A Unified Factorization model for predicting retweet behaviors.INFORMATION SCIENCES,515,218-232.
MLA	Wang, Shaoqing,et al."BPF plus plus : A Unified Factorization model for predicting retweet behaviors".INFORMATION SCIENCES 515(2020):218-232.