Location Prediction: A Temporal-Spatial Bayesian Model

doi:10.1145/2816824

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

	Location Prediction: A Temporal-Spatial Bayesian Model
	Jia, Yantao; Wang, Yuanzhuo; Jin, Xiaolong; Cheng, Xueqi
刊名	ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
	2016-04-01
卷号	7 期号:3 页码:25
关键词	Design Algorithms Performance Location prediction influential friends dynamic selection temporal-spatial evolution dynamic Bayesian network
ISSN号	2157-6904
DOI	10.1145/2816824
英文摘要	In social networks, predicting a user's location mainly depends on those of his/her friends, where the key lies in how to select his/her most influential friends. In this article, we analyze the theoretically maximal accuracy of location prediction based on friends' locations and compare it with the practical accuracy obtained by the state-of-the-art location prediction methods. Upon observing a big gap between the theoretical and practical accuracy, we propose a new strategy for selecting influential friends in order to improve the practical location prediction accuracy. Specifically, several features are defined to measure the influence of the friends on a user's location, based on which we put forth a sequential random-walk-with-restart procedure to rank the friends of the user in terms of their influence. By dynamically selecting the top N most influential friends of the user per time slice, we develop a temporal-spatial Bayesian model to characterize the dynamics of friends' influence for location prediction. Finally, extensive experimental results on datasets of real social networks demonstrate that the proposed influential friend selection method and temporal-spatial Bayesian model can significantly improve the accuracy of location prediction.
资助项目	National Program (973 Program) on Key Basic Research Project of China[2013CB329602] ; National Program (973 Program) on Key Basic Research Project of China[2012CB316303] ; National Natural Science Foundation of China[61173008] ; National Natural Science Foundation of China[61100175] ; National Natural Science Foundation of China[61232010] ; National Natural Science Foundation of China[61303244] ; National Natural Science Foundation of China[61402442] ; Beijing Nova Program[Z121101002512063] ; Beijing Natural Science Foundation[4154086]
WOS研究方向	Computer Science
语种	英语
出版者	ASSOC COMPUTING MACHINERY
WOS记录号	WOS:000373911200006
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/8471]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Jia, Yantao; Wang, Yuanzhuo; Jin, Xiaolong; Cheng, Xueqi
作者单位	Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Jia, Yantao,Wang, Yuanzhuo,Jin, Xiaolong,et al. Location Prediction: A Temporal-Spatial Bayesian Model[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2016,7(3):25.
APA	Jia, Yantao,Wang, Yuanzhuo,Jin, Xiaolong,&Cheng, Xueqi.(2016).Location Prediction: A Temporal-Spatial Bayesian Model.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,7(3),25.
MLA	Jia, Yantao,et al."Location Prediction: A Temporal-Spatial Bayesian Model".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 7.3(2016):25.