BERT4Loc: BERT for Location—POI Recommender System

Recommending points of interest (POI) is a challenging task that requires extracting comprehensive location data from location-based social media platforms. To provide effective recommendations, it important to analyze users’ historical behavior and preferences. In this study, we present sophisticated location-aware recommendation system uses Bidirectional Encoder Representations Transformers (BERT) offer personalized suggestions. Our model combines information user preferences more relevant recommendations compared models predict the next POI in sequence. Based on our experiments conducted two benchmark datasets, have observed BERT-based surpasses baselines terms HR by significant margin 6% second-best performing baseline. Furthermore, demonstrates percentage gain 1–2% NDCG second best These results indicate superior performance effectiveness approach comparison other when evaluating metrics. Moreover, see proposed for quality through additional experiments.