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008			230714s2023 sz | o |1|| 0|eng d
020			_a9783031372490
024	7		_a10.1007/978-3-031-37249-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aZA3075 _b2023 EB
245	0	0	_aAdvances in Bias and Fairness in Information Retrieval : _b4th International Workshop, BIAS 2023, Dublin, Ireland, April 2, 2023, Revised Selected Papers _cedited by Ludovico Boratto, Stefano Faralli, Mirko Marras, Giovanni Stilo
250			_a1st ed 2023
264		1	_aCham _bSpringer Nature Switzerland _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aCommunications in Computer and Information Science _x1865-0937 _v1840
505	0		_aA 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.
520			_aThis 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.
988			_aSpringer_Computer_2023
650		7	_2embne _9147823 _aRecuperación de la información _vCongresos y asambleas
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-37249-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2024 _dz _eb _zSI