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Friend Recommendation Using Offline and Online Social Information for Face-To-Face Interactions

机译:朋友推荐使用离线和在线社交信息进行面对面的互动

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The combination of online social networking services (OSNSs) and the smartphones has changed the ways to acquire information and also influenced the ways people get to know and interact with each other. Despite with many advanced functions, online social interactions can hardly provide online social users with real-world (i.e., offline) social interactions. In this paper, we present an offline friend recommendation system for the OSNS users to have more serendipitous offline interactions. For that, we modeled both offline information (i.e., place visit history) and online social data (i.e., friend relationships) for recommending their offline interactions. Our system discovers those who seems most likely to have potential friend relationship so as to meet in the physical world. We present the design and implementation of our proposed system and conduct real-world experiment to show how the place visit information and online friend relationship together produce a new offline social networking service.
机译:在线社交网络服务(OSNS)和智能手机的结合改变了获取信息的方式,也影响了人们彼此了解和互动的方式。尽管具有许多高级功能,但在线社交互动几乎无法为在线社交用户提供现实世界(即离线)社交互动。在本文中,我们为OSNS用户提供了一个离线好友推荐系统,以使他们具有更多偶然的离线互动。为此,我们对离线信息(例如,访问历史记录)和在线社交数据(即,朋友关系)进行了建模,以推荐他们的离线互动。我们的系统会发现那些似乎最有可能建立潜在朋友关系的人,以便在物理世界中结识。我们介绍了我们提出的系统的设计和实现,并进行了真实的实验,以显示地点访问信息和在线朋友关系如何共同产生新的离线社交网络服务。

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