ACTPred: Activity Prediction in Mobile Social Networks

查看全文 作　　者：Jibing [1]Gong;Jie [2]Tang;A.C.M. [3]Fong

机构地区：[1]School of Information Science and Engineering, Yanshan University;[2]Department of Computer Science and Technology, Tsinghua University;[3]University of Glasgow in Singapore

出　　处：《Tsinghua Science and Technology》索引2014年第19卷第3期,共10页

基　　金：supported by the National HighTech Research and Development (863) Program of China (No. 2014AA015103);the National Key Basic Research and Development (973) Program of China (Nos. 2014CB340500 and 2012CB316006);the National Natural Science Foundation of China (No. 61222212);the Tsinghua University Initiative Scientific Research Program (No. 20121088096);supported by Huawei Inc. and Beijing key lab of networked multimedia 摘　　要：A current trend for online social networks is to turn mobile. Mobile social networks directly reflect our real social life, and therefore are an important source to analyze and understand the underlying dynamics of human behaviors(activities). In this paper, we study the problem of activity prediction in mobile social networks. We present a series of observations in two real mobile social networks and then propose a method, ACTPred, based on a dynamic factor-graph model for modeling and predicting users' activities. An approximate algorithm based on mean fields is presented to efficiently learn the proposed method. We deploy a real system to collect users' mobility behaviors and validate the proposed method on two collected mobile datasets. Experimental results show that the proposed ACTPred model can achieve better performance than baseline methods. 关键词：移动性网络社交预报人类行为社会生活研究活动动态因子

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ACTPred: Activity Prediction in Mobile Social Networks

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