Context-Aware POI Sequence Recommendation with Attention-Based Neural Network
Keywords: POI Sequence recommendation, Attention-Based Neural Network, Location-based social networks
Abstract. Location-based social networks (LBSNs) is playing an increasingly important role in our daily life, through which users can share their locations and location-related contents at any time. The Location information implicitly expresses user's behaviour preference. Therefore, LBSNs is being widely explored for Point-of-Interest (POI) recommendation in recent years. Most of existing POI recommenders only recommend a single POI, while sometimes successive POI sequence recommendation is more practical. For example, when we travel to a strange city, what we expect is not a single POI recommendation, but a POI sequence recommendation which contains a set of POIs and the order of visiting them. To solve this problem, this paper proposes a novel model called Context-Aware POI Sequence Recommendation (CPSR), which is developed based on an attention-based neural network. Neural network has made a great success in various of field because of its powerful learning ability. Recently, dozens of works has demonstrated that attention mechanism can make the neural network models more reasonable.