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Lecture Notes in Computer Science
Point-of-Interest (POI) recommendation is one of the most important location-based services helping people discover interesting venues or services. However, the extreme user-POI matrix sparsity and the varying spatio-temporal context pose challenges for POI systems, which affects the quality of POI recommendations. To this end, we propose a translation-based relation embedding for POI recommendation. Our approach encodes the temporal and geographic information, as well as semantic contentsdoi:10.1007/978-3-030-47426-3_5 fatcat:zron5negfbea5lqfgnmz6rimuq