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20232025
most citedTowards Individual and Multistakeholder Fairness in Tourism Recommender Systems

32 citations · 75 across the 8 of their papers we have counts for

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Showing cs.IRShow all

5 papers · 1 filter

cs.IR2025★ 4 cited

SynthTRIPs: A Knowledge-Grounded Framework for Benchmark Query Generation for Personalized Tourism Recommenders

Ashmi Banerjee, Adithi Satish, Fitri Nur Aisyah +2

Tourism Recommender Systems (TRS) are crucial in personalizing travel experiences by tailoring recommendations to users' preferences, constraints, and contextual factors. However,…

cs.IR2024★ 16 cited

Enhancing Tourism Recommender Systems for Sustainable City Trips Using Retrieval-Augmented Generation

Ashmi Banerjee, Adithi Satish, Wolfgang Wörndl

Tourism Recommender Systems (TRS) have traditionally focused on providing personalized travel suggestions, often prioritizing user preferences without considering broader sustainab…

cs.IR2024★ 19 cited

Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender Systems

Ashmi Banerjee, Tunar Mahmudov, Emil Adler +2

Tourism affects not only the tourism industry but also society and stakeholders such as the environment, local businesses, and residents. Tourism Recommender Systems (TRS) can be p…

cs.IR2023★ 32 cited

Towards Individual and Multistakeholder Fairness in Tourism Recommender Systems

Ashmi Banerjee, Paromita Banik, Wolfgang Wörndl

This position paper summarizes our published review on individual and multistakeholder fairness in Tourism Recommender Systems (TRS). Recently, there has been growing attention to…

cs.IR2023★ 2 cited

Dynamic Adaptation of User Preferences and Results in a Destination Recommender System

Asal Nesar Noubari, Wolfgang Wörndl

Studying human factors has gained a lot of interest in recommender systems research recently. User experience plays a vital role in tourism recommender systems since user satisfact…