Publikation: Fairness in recommender systems: resear...
Stammdaten
Titel: | Fairness in recommender systems: research landscape and future directions |
Untertitel: | |
Kurzfassung: | Recommender systems can strongly influence which information we see online, e.g., on social media, and thus impact our beliefs, decisions, and actions. At the same time, these systems can create substantial business value for different stakeholders. Given the growing potential impact of such AI-based systems on individuals, organizations, and society, questions of fairness have gained increased attention in recent years. However, research on fairness in recommender systems is still a developing area. In this survey, we first review the fundamental concepts and notions of fairness that were put forward in the area in the recent past. Afterward, through a review of more than 160 scholarly publications, we present an overview of how research in this field is currently operationalized, e.g., in terms of general research methodology, fairness measures, and algorithmic approaches. Overall, our analysis of recent works points to certain research gaps. In particular, we find that in many research works in computer science, very abstract problem operationalizations are prevalent and questions of the underlying normative claims and what represents a fair recommendation in the context of a given application are often not discussed in depth. These observations call for more interdisciplinary research to address fairness in recommendation in a more comprehensive and impactful manner. |
Schlagworte: | Computer Science Applications, Human-Computer Interaction, Education |
Publikationstyp: | Beitrag in Zeitschrift (Autorenschaft) |
Erscheinungsdatum: | 24.04.2023 (Online) |
Erschienen in: |
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
(
Springer Verlag GmbH;
)
zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Heftnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 1 - 50 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 24.04.2023 |
ISBN (e-book): | - |
eISSN: | 1573-1391 |
DOI: | http://dx.doi.org/10.1007/s11257-023-09364-z |
Homepage: | - |
Open Access |
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AutorInnen
Yashar Deldjoo (extern) |
Dietmar Jannach (intern) |
Alejandro Bellogin (extern) |
Alessandro Difonzo (extern) |
Dario Zanzonelli (extern) |
Zuordnung
Organisation | Adresse | ||||
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Fakultät für Technische Wissenschaften
Institut für Artificial Intelligence und Cybersecurity
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AT - A-9020 Klagenfurt |
Kategorisierung
Sachgebiete | |
Forschungscluster |
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Zitationsindex |
Informationen zum Zitationsindex: Master Journal List
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Peer Reviewed |
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Publikationsfokus |
Klassifikationsraster der zugeordneten Organisationseinheiten:
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Arbeitsgruppen |
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Kooperationen
Organisation | Adresse | ||
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Politecnico di Bari
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IT - 70125 Bari |
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Universidad Autónoma De Madrid
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ES
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Forschungsaktivitäten
(Achtung: Externe Aktivitäten werden im Suchergebnis nicht mitangezeigt)
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