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

文献类型：期刊论文

作者Wang, Shaoqing1; Li, Cuipin2; Wang, Zheng3; Chen, Hong2; Zheng, Kai4
刊名INFORMATION SCIENCES
出版日期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
DOI10.1016/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
WOS记录号WOS:000513293200013
出版者ELSEVIER SCIENCE INC
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.

入库方式： OAI收割

来源：计算技术研究所

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