Green Destination Recommender: A Web Application to Encourage Responsible City Trip Recommendations

Ashmi Banerjee, Tunar Mahmudov, Wolfgang Wörndl

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Tourism Recommender Systems (TRS) have evolved from only providing user recommendations to becoming convergence points for multiple stakeholders. This necessitates recognizing the interests of all stakeholders, particularly in the tourism sector, which faces challenges like seasonality and resource constraints. Our stakeholder classification identifies consumers, item providers, platform, and society as key stakeholders, highlighting the complexity of real-world relationships. Fairness in TRS demands a multistakeholder approach, integrating sustainability to address the broader societal impact. While research has focused on fair recommendation systems in tourism, the focus on generating sustainable recommendations remains limited. This demo paper aims to enhance fairness in TRS, mainly focusing on society as a stakeholder. We introduce the Green Destination Recommender (GDR), an application that prioritizes Societal Fairness (S-Fairness) by encouraging environmentally conscious decisions. GDR recommends sustainable tourism destinations based on the user's starting location, travel month, and specific interests. The application promotes ecologically friendly options by recommending less popular yet appealing destinations, considering the emissions from transport to reach the destination and the seasonal demand to balance visitor numbers year-round.

Original languageEnglish
Title of host publicationUMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
PublisherAssociation for Computing Machinery, Inc
Pages486-490
Number of pages5
ISBN (Electronic)9798400704666
DOIs
StatePublished - 27 Jun 2024
Event32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024 - Cagliari, Italy
Duration: 1 Jul 20244 Jul 2024

Publication series

NameUMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization

Conference

Conference32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024
Country/TerritoryItaly
CityCagliari
Period1/07/244/07/24

Keywords

  • Multistakeholder Fairness
  • Societal Fairness
  • Sustainability
  • Tourism Recommender Systems

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