Titlebook: Spatio-Temporal Recommendation in Social Media; Hongzhi Yin,Bin Cui Book 2016 Springer Science+Business Media Singapore 2016 Recommander s

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Introduction,ch issues and challenges emerging in this field, including Temporal Context-Aware Recommendation, Spatial Recommendation for Out-of-Town Users, Location-based and Real-time Recommendation, and the Efficiency of Online Recommendation. We overview this book by listing our basic solution ideas for thes

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Temporal Context-Aware Recommendation,at that time). In this chapter, we focus on analyzing user behaviors in social media systems and designing a latent class statistical mixture model, named . (TCAM), to account for the intentions and preferences behind user behaviors. TCAM simultaneously models the topics related to users’ intrinsic

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Spatial Context-Aware Recommendation,which creates a big challenge for traditional collaborative filtering-based recommender systems. The problem becomes more challenging when people travel to a new city where they have no activity history. In this chapter, we propose LCARS, a location-content-aware recommender system that offers a par

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