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Advances in bias and fairness in information retrieval = 5th International Workshop, BIAS 2024, Washington, DC, USA, July 18, 2024 : revised selected papers /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in bias and fairness in information retrieval/ edited by Alejandro Bellogin ... [et al.].
Reminder of title:	5th International Workshop, BIAS 2024, Washington, DC, USA, July 18, 2024 : revised selected papers /
remainder title:	BIAS 2024
other author:	Bellogin, Alejandro.
corporate name:	International Workshop on Algorithmic Bias in Search and Recommendation
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	ix, 103 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	An Offer you Cannot Refuse? Trends in the Coercive Impact of Amazon Book Recommendations -- Retention Induced Biases in a Recommendation System with Heterogeneous Users -- Political Bias of Large Language Models in Few-shot News Summarization -- Fairness Analysis of Machine Learning-Based Code Reviewer Recommendation -- Bias Reduction in Social Networks through Agent-Based Simulations -- vivaFemme: Mitigating Gender Bias in Neural Team Recommendation via Female-Advocate Loss Regularization -- Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training.
Contained By:	Springer Nature eBook
Subject:	Information retrieval - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-031-71975-2
ISBN:	9783031719752

Advances in bias and fairness in information retrieval = 5th International Workshop, BIAS 2024, Washington, DC, USA, July 18, 2024 : revised selected papers /
Advances in bias and fairness in information retrieval5th International Workshop, BIAS 2024, Washington, DC, USA, July 18, 2024 : revised selected papers /[electronic resource] :BIAS 2024edited by Alejandro Bellogin ... [et al.]. - Cham :Springer Nature Switzerland :2025. - ix, 103 p. :ill. (some col.), digital ;24 cm. - Communications in computer and information science,22271865-0937 ;. - Communications in computer and information science ;2227..

An Offer you Cannot Refuse? Trends in the Coercive Impact of Amazon Book Recommendations -- Retention Induced Biases in a Recommendation System with Heterogeneous Users -- Political Bias of Large Language Models in Few-shot News Summarization -- Fairness Analysis of Machine Learning-Based Code Reviewer Recommendation -- Bias Reduction in Social Networks through Agent-Based Simulations -- vivaFemme: Mitigating Gender Bias in Neural Team Recommendation via Female-Advocate Loss Regularization -- Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training.

This book constitutes the refereed proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2024, held in Washington, DC, USA, on July 18, 2024 in hybrid mode. The 7 full papers included in this book were carefully reviewed and selected from 20 submissions. They are grouped into three thematic sessions, each focusing on distinct aspects of bias and fairness in information retrieval.

ISBN: 9783031719752

Standard No.: 10.1007/978-3-031-71975-2doiSubjects--Topical Terms:

884379
Information retrieval
--Congresses.

LC Class. No.: ZA3075 / .I48 2024

Dewey Class. No.: 025.04

Advances in bias and fairness in information retrieval = 5th International Workshop, BIAS 2024, Washington, DC, USA, July 18, 2024 : revised selected papers /
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505 0 $a An Offer you Cannot Refuse? Trends in the Coercive Impact of Amazon Book Recommendations -- Retention Induced Biases in a Recommendation System with Heterogeneous Users -- Political Bias of Large Language Models in Few-shot News Summarization -- Fairness Analysis of Machine Learning-Based Code Reviewer Recommendation -- Bias Reduction in Social Networks through Agent-Based Simulations -- vivaFemme: Mitigating Gender Bias in Neural Team Recommendation via Female-Advocate Loss Regularization -- Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training.
520 $a This book constitutes the refereed proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2024, held in Washington, DC, USA, on July 18, 2024 in hybrid mode. The 7 full papers included in this book were carefully reviewed and selected from 20 submissions. They are grouped into three thematic sessions, each focusing on distinct aspects of bias and fairness in information retrieval.
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