A Survey on Point-of-Interest Recommendations Leveraging Heterogeneous Data
arXiv:2308.07426 · doi:10.1007/s40558-024-00301-3
Abstract
Tourism is an important application domain for recommender systems. In this domain, recommender systems are for example tasked with providing personalized recommendations for transportation, accommodation, points-of-interest (POIs), etc. Among these tasks, in particular the problem of recommending POIs that are of likely interest to individual tourists has gained growing attention in recent years. Providing POI recommendations to tourists can however be especially challenging due to the variability of the user's context. With the rapid development of the Web and today's multitude of online services, vast amounts of data from various sources have become available, and these heterogeneous data represent a huge potential to better address the challenges of POI recommendation problems. In this work, we provide a survey of published research on the problem of POI recommendation between 2021 and 2023. The literature was surveyed to identify the information types, techniques and evaluation methods employed. Based on the analysis, it was observed that the current research tends to focus on a relatively narrow range of information types and there is a significant potential in improving POI recommendation by leveraging heterogeneous data. As the first information-centric survey on POI recommendation research, this study serves as a reference for researchers aiming to develop increasingly accurate, personalized and context-aware POI recommender systems.
References in corpus (16)
- YFCC100M: The New Data in Multimedia Research
- Recommender Systems
- A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
- STAN: Spatio-Temporal Attention Network for Next Location Recommendation
- Measuring the Business Value of Recommender Systems
- Fairness in Recommender Systems: Research Landscape and Future Directions
- A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research
- Empirical Analysis of Session-Based Recommendation Algorithms
- Offline A/B testing for Recommender Systems
- Point-of-Interest Recommender Systems based on Location-Based Social Networks: A Survey from an Experimental Perspective
- DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation
- Evaluating Conversational Recommender Systems: A Landscape of Research
- The General Data Protection Regulation: Requirements, Architectures, and Constraints
- Tag Embedding Based Personalized Point Of Interest Recommendation System
- Using consumer feedback from location-based services in PoI recommender systems for people with autism
- Eliciting Touristic Profiles: A User Study on Picture Collections