Contextual Fairness; Fusion; POI; Recommender Systems; Check-in; Context-aware recommendation algorithms; Contextual fairness; Contextual information; Point-of-interest; Primary objective; Research communities; Temporal bias; Traffic-related air pollution; Work hours; Hardware and Architecture; Software; Computer Science - Information Retrieval
Résumé :
[en] Recommending appropriate travel destinations to consumers based on contextual information such as their check-in time and location is a primary objective of Point-of-Interest (POI) recommender systems. However, the issue of contextual bias (i.e., how much consumers prefer one situation over another) has received little attention from the research community. This paper examines the effect of temporal bias, defined as the difference between users' check-in hours, leisure vs. work hours, on the consumer-side fairness of context-aware recommendation algorithms. We believe that eliminating this type of temporal (and geographical) bias might contribute to a drop in traffic-related air pollution, noting that rush-hour traffic may be more congested. To surface effective POI recommendation, we evaluated the sensitivity of state-of-the-art context-aware models to the temporal bias contained in users' check-in activities on two POI datasets, namely Gowalla and Yelp. The findings show that the examined context-aware recommendation models prefer one group of users over another based on the time of check-in and that this preference persists even when users have the same amount of interactions.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > ARG - Automation & Robotics
Disciplines :
Sciences informatiques
Auteur, co-auteur :
Rahmani, Hossein A.; Wi, University College London, United Kingdom
Naghiaei, Mohammadmehdi; Ise Department, University of Southern California, United States
TOURANI, Ali ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
Deldjoo, Yashar; Polytechnic University of Bari, Italy
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation
Date de publication/diffusion :
12 septembre 2022
Nom de la manifestation :
ACM INTERNATIONAL CONFERENCE ON RECOMMENDER SYSTEMS
Lieu de la manifestation :
Seattle, Usa
Date de la manifestation :
18-23 September 2022
Manifestation à portée :
International
Titre de l'ouvrage principal :
RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems
ACM Special Interest Group on Artificial Intelligence (SIGAI) ACM Special Interest Group on Computer-Human Interaction (SIGCHI) ACM Special Interest Group on Hypertext, Hypermedia, and Web (SIGWEB) ACM Special Interest Group on Information Retrieval (SIGIR) ACM Special Interest Group on Knowledge Discovery in Data (SIGKDD)
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