04094nam 22006255 450 99654682540331620230714050258.03-031-37249-210.1007/978-3-031-37249-0(MiAaPQ)EBC30645962(Au-PeEL)EBL30645962(DE-He213)978-3-031-37249-0(PPN)272251291(EXLCZ)992756516130004120230714d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdvances in Bias and Fairness in Information Retrieval[electronic resource] 4th International Workshop, BIAS 2023, Dublin, Ireland, April 2, 2023, Revised Selected Papers /edited by Ludovico Boratto, Stefano Faralli, Mirko Marras, Giovanni Stilo1st ed. 2023.Cham :Springer Nature Switzerland :Imprint: Springer,2023.1 online resource (187 pages)Communications in Computer and Information Science,1865-0937 ;1840Print version: Boratto, Ludovico Advances in Bias and Fairness in Information Retrieval Cham : Springer International Publishing AG,c2023 9783031372483 A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations -- Measuring Bias in Multimodal Models: Multimodal Composite Association Score -- Evaluating Fairness Metrics -- Utilizing Implicit Feedback for User Mainstreaminess Evaluation and Bias Detection in Recommender Systems -- Preserving Utility in Fair Top-k Ranking with Intersectional Bias -- Mitigating Position Bias in Hotels Recommender Systems -- Improving Recommender System Diversity with Variational Autoencoders -- Addressing Biases in the Texts using an End-to-End Pipeline Approach -- Bootless Application of Greedy Re-ranking Algorithms in Fair Neural Team Formation -- How do you feel? Information Retrieval in Psychotherapy and Fair Ranking Assessment -- Understanding Search Behavior Bias in Wikipedia -- Do you MIND? Reflections on the MIND dataset for research on diversity in news recommendations -- Detecting and Measuring Social Bias of Arabic Generative Models in the Context of Search and Recommendation -- What are we missing in algorithmic fairness? Discussing open challenges for fairness analysis in user profiling with Graph Neural Networks.This book constitutes the refereed proceedings of the 4th International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2023, held in Dublin, Ireland, in April 2023. The 10 full papers and 4 short papers included in this book were carefully reviewed and selected from 36 submissions. The present recent research in the following topics: biases exploration and assessment; mitigation strategies against biases; biases in newly emerging domains of application, including healthcare, Wikipedia, and news, novel perspectives; and conceptualizations of biases in the context of generative models and graph neural networks.Communications in Computer and Information Science,1865-0937 ;1840Computer engineeringComputer networksArtificial intelligenceElectronic commerceComputer Engineering and NetworksArtificial Intelligencee-Commerce and e-BusinessComputer engineering.Computer networks.Artificial intelligence.Electronic commerce.Computer Engineering and Networks.Artificial Intelligence.e-Commerce and e-Business.025.524Boratto Ludovico1373698Faralli Stefano1373699Marras Mirko1373700Stilo Giovanni1373701MiAaPQMiAaPQMiAaPQBOOK996546825403316Advances in Bias and Fairness in Information Retrieval3404763UNISA