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  • © 2022

Advances in Bias and Fairness in Information Retrieval

Third International Workshop, BIAS 2022, Stavanger, Norway, April 10, 2022, Revised Selected Papers

Conference proceedings info: BIAS 2022.

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Table of contents (13 papers)

  1. Front Matter

    Pages i-x
  2. The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation

    • Hossein A. Rahmani, Yashar Deldjoo, Ali Tourani, Mohammadmehdi Naghiaei
    Pages 56-68
  3. The Unfairness of Popularity Bias in Book Recommendation

    • Mohammadmehdi Naghiaei, Hossein A. Rahmani, Mahdi Dehghan
    Pages 69-81
  4. Mitigating Popularity Bias in Recommendation: Potential and Limits of Calibration Approaches

    • Anastasiia Klimashevskaia, Mehdi Elahi, Dietmar Jannach, Christoph Trattner, Lars Skjærven
    Pages 82-90
  5. Analysis of Biases in Calibrated Recommendations

    • Carlos Rojas, David Contreras, Maria Salamó
    Pages 91-103
  6. Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements?

    • Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz
    Pages 104-116
  7. Enhancing Fairness in Classification Tasks with Multiple Variables: A Data- and Model-Agnostic Approach

    • Giordano d’Aloisio, Giovanni Stilo, Antinisca Di Marco, Andrea D’Angelo
    Pages 117-129
  8. Keyword Recommendation for Fair Search

    • Harshit Mishra, Sucheta Soundarajan
    Pages 130-142
  9. FARGO: A Fair, Context-AwaRe, Group RecOmmender System

    • Davide Azzalini, Elisa Quintarelli, Emanuele Rabosio, Letizia Tanca
    Pages 143-154
  10. Back Matter

    Pages 155-155

Other Volumes

  1. Advances in Bias and Fairness in Information Retrieval

About this book

This book constitutes refereed proceedings of the Third International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2022, held in April, 2022. 

The 9 full papers and 4 short papers were carefully reviewed and selected from 34 submissions. The papers cover topics that go from search and recommendation in online dating, education, and social media, over the impact of gender bias in word embeddings, to tools that allow to explore bias and fairnesson the Web. 

Keywords

  • artificial intelligence
  • collaborative filtering
  • computer networks
  • computer systems
  • electronic commerce
  • Human-Computer Interaction (HCI)
  • information retrieval
  • machine learning
  • network protocols
  • personalizations
  • recommendation algorithms
  • recommendation systems
  • recommender systems
  • search engines
  • user interfaces

Editors and Affiliations

  • University of Cagliari, Cagliari, Italy

    Ludovico Boratto, Mirko Marras

  • Sapienza University of Rome, Rome, Italy

    Stefano Faralli

  • University of L’Aquila, L’Aquila, Italy

    Giovanni Stilo

Bibliographic Information

Buy it now

Buying options

eBook USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access