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arXiv · 2208.01375

BERT4Loc: BERT for Location -- POI Recommender System

Syed Raza Bashir·Shaina Raza·Vojislav Misic
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Abstract

Recommending points of interest (POIs) is a challenging task that requires extracting comprehensive location data from location-based social media platforms. To provide effective location-based recommendations, it's important to analyze users' historical behavior and preferences. In this study, we present a sophisticated location-aware recommendation system that uses Bidirectional Encoder Representations from Transformers (BERT) to offer personalized location-based suggestions. Our model combines location information and user preferences to provide more relevant recommendations compared to models that predict the next POI in a sequence. Our experiments on two benchmark dataset show that our BERT-based model outperforms various state-of-the-art sequential models. Moreover, we see the effectiveness of the proposed model for quality through additional experiments.

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Syed Raza Bashir, Shaina Raza, Vojislav Misic. 2022-08-02. BERT4Loc: BERT for Location -- POI Recommender System. https://arxiv.org/abs/2208.01375

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