Towards Individual and Multistakeholder Fairness in Tourism Recommender Systems

Abstract

This position paper summarizes our published review on individual and multistakeholder fairness in Tourism Recommender Systems (TRS). Recently, there has been growing attention to fairness considerations in recommender systems (RS). It has been acknowledged in research that fairness in RS is often closely tied to the presence of multiple stakeholders, such as end users, item providers, and platforms, as it raises concerns for the fair treatment of all parties involved. Hence, fairness in RS is a multi-faceted concept that requires consideration of the perspectives and needs of the different stakeholders to ensure fair outcomes for them. However, there may often be instances where achieving the goals of one stakeholder could conflict with those of another, resulting in trade-offs. In this paper, we emphasized addressing the unique challenges of ensuring fairness in RS within the tourism domain. We aimed to discuss potential strategies for mitigating the aforementioned challenges and examine the applicability of solutions from other domains to tackle fairness issues in tourism. By exploring cross-domain approaches and strategies for incorporating S-Fairness, we can uncover valuable insights and determine how these solutions can be adapted and implemented effectively in the context of tourism to enhance fairness in RS.

Position Paper for FAcctRec 2023 at RecSys 2023

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Cited by in corpus (5)

• Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender Systems
• Enhancing Tourism Recommender Systems for Sustainable City Trips Using Retrieval-Augmented Generation
• Multistakeholder Fairness in Tourism: What can Algorithms learn from Tourism Management?
• Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations
• Point of Interest Recommendation: Pitfalls and Viable Solutions