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ORCIDBIAS 2023: Dublin, Ireland
- Ludovico Boratto
, Stefano Faralli, Mirko Marras, Giovanni Stilo:
Advances in Bias and Fairness in Information Retrieval - 4th International Workshop, BIAS 2023, Dublin, Ireland, April 2, 2023, Revised Selected Papers. Communications in Computer and Information Science 1840, Springer 2023, ISBN 978-3-031-37248-3 - Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex:
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. 1-16 - Abhishek Mandal, Susan Leavy, Suzanne Little:
Measuring Bias in Multimodal Models: Multimodal Composite Association Score. 17-30 - Zahid Irfan, Fergal McCaffery, Róisín Loughran:
Evaluating Fairness Metrics. 31-41 - Kuanyi Zhang, Min Xie, Yi Zhang, Haixian Zhang:
Utilizing Implicit Feedback for User Mainstreaminess Evaluation and Bias Detection in Recommender Systems. 42-58 - Nicola Alimonda, Alessandro Castelnovo, Riccardo Crupi, Fabio Mercorio, Mario Mezzanzanica:
Preserving Utility in Fair Top-k Ranking with Intersectional Bias. 59-73 - Yinxiao Li:
Mitigating Position Bias in Hotels Recommender Systems. 74-84 - Sheetal Borar, Hilde J. P. Weerts, Binyam Gebre, Mykola Pechenizkiy:
Improving Recommender System Diversity with Variational Autoencoders. 85-99 - Shaina Raza, Syed Raza Bashir, Sneha, Urooj Qamar:
Addressing Biases in the Texts Using an End-to-End Pipeline Approach. 100-107 - Hamed Loghmani, Hossein Fani:
Bootless Application of Greedy Re-ranking Algorithms in Fair Neural Team Formation. 108-118 - Vivek Kumar, Giacomo Medda, Diego Reforgiato Recupero, Daniele Riboni, Rim Helaoui, Gianni Fenu:
How Do You Feel? Information Retrieval in Psychotherapy and Fair Ranking Assessment. 119-133 - Bruno Scarone, Ricardo Baeza-Yates, Erik Bernhardson:
Understanding Search Behavior Bias in Wikipedia. 134-146 - Sanne Vrijenhoek:
Do You MIND? Reflections on the MIND Dataset for Research on Diversity in News Recommendations. 147-154 - Fouzi Harrag, Chaima Mahdadi, Amina Nourhane Ziad:
Detecting and Measuring Social Bias of Arabic Generative Models in the Context of Search and Recommendation. 155-168 - Erasmo Purificato, Ernesto William De Luca:
What Are We Missing in Algorithmic Fairness? Discussing Open Challenges for Fairness Analysis in User Profiling with Graph Neural Networks. 169-175
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