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  • 标题:Friendship prediction model based on factor graphs integrating geographical location
  • 本地全文:下载
  • 作者:Liang Chen ; Shaojie Qiao ; Nan Han
  • 期刊名称:CAAI Transactions on Intelligence Technology
  • 电子版ISSN:2468-2322
  • 出版年度:2020
  • 卷号:5
  • 期号:3
  • 页码:193-199
  • DOI:10.1049/trit.2020.0033
  • 出版社:IET Digital Library
  • 摘要:With the development of network services and location-based systems, many mobile applications begin to use users’ geographical location to provide better services. In terms of social networks, geographical location is actively shared by users. In some applications with recommendation services, before the geographical location recommendation is provided, the authors have to obtain user's permission. This kind of social network integrated with geographical location information is called location-based social networks (abbreviate for LBSNs). In the LBSN, each user has location information when he or she checked in hotels or feature spots. Based on this information, they can identify user's trajectory of movement behaviour and activity patterns. In general, if there is friendship between two users, their trajectories in reality are likely to be similar. In this study, according to user's geographical location information over a period of time, they explore whether there exists friendly relationship between two users based on trajectory similarity and the structure theory of graphs. In particular, they propose a new factor function and a factor graph model based on user's geographical location to predict the friendship between two users in the real LBSN.
  • 关键词:structure theory; geographical location information; geographical location recommendation; activity patterns; trajectory similarity; friendship prediction model; movement behaviour; location-based social networks; network services; location-based systems; recommendation services; factor graph model; social network
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