- Mohammadmehdi Naghiaei
, Hossein A. Rahmani, Mahdi Dehghan:
The Unfairness of Popularity Bias in Book Recommendation. BIAS 2022: 69-81 - Julia Neidhardt, Mete Sertkan:
Towards an Approach for Analyzing Dynamic Aspects of Bias and Beyond-Accuracy Measures. BIAS 2022: 35-42 - Hossein A. Rahmani, Yashar Deldjoo, Ali Tourani, Mohammadmehdi Naghiaei:
The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation. BIAS 2022: 56-68 - Carlos Rojas, David Contreras, Maria Salamó:
Analysis of Biases in Calibrated Recommendations. BIAS 2022: 91-103 - Ali Shirali:
Sequential Nature of Recommender Systems Disrupts the Evaluation Process. BIAS 2022: 21-34 - Giordano d'Aloisio, Giovanni Stilo, Antinisca Di Marco, Andrea D'Angelo:
Enhancing Fairness in Classification Tasks with Multiple Variables: A Data- and Model-Agnostic Approach. BIAS 2022: 117-129 - Ludovico Boratto, Stefano Faralli, Mirko Marras, Giovanni Stilo:
Advances in Bias and Fairness in Information Retrieval - Third International Workshop, BIAS 2022, Stavanger, Norway, April 10, 2022, Revised Selected Papers. Communications in Computer and Information Science 1610, Springer 2022, ISBN 978-3-031-09315-9 [contents] - 2021
- Michael Färber, Frederic Bartscherer:
Media Bias Everywhere? A Vision for Dealing with the Manipulation of Public Opinion. BIAS 2021: 9-13 - Elena Beretta, Antonio Vetrò, Bruno Lepri, Juan Carlos De Martin:
Equality of Opportunity in Ranking: A Fair-Distributive Model. BIAS 2021: 51-63 - Yunhe Feng, Daniel Saelid, Ke Li, Ruoyuan Gao, Chirag Shah:
Towards Fairness-Aware Ranking by Defining Latent Groups Using Inferred Features. BIAS 2021: 1-8 - Francisco Guíñez, Javier Ruiz, María Ignacia Sánchez:
Quantification of the Impact of Popularity Bias in Multi-stakeholder and Time-Aware Environments. BIAS 2021: 78-91 - Fabian Haak, Philipp Schaer:
Perception-Aware Bias Detection for Query Suggestions. BIAS 2021: 130-142 - Bin Han, Chirag Shah, Daniel Saelid:
Users' Perception of Search-Engine Biases and Satisfaction. BIAS 2021: 14-24 - Chenyu Jiang, Bowen Wu, Sanghamitra Dutta, Pulkit Grover:
An Information-Theoretic Measure for Enabling Category Exemptions with an Application to Filter Bubbles. BIAS 2021: 117-129 - Toshihiro Kamishima, Shotaro Akaho, Yukino Baba, Hisashi Kashima:
Preliminary Experiments to Examine the Stability of Bias-Aware Techniques. BIAS 2021: 25-35 - Baris Kirdemir, Joseph Kready, Esther Mead, Muhammad Nihal Hussain, Nitin Agarwal:
Examining Video Recommendation Bias on YouTube. BIAS 2021: 106-116 - Tobias D. Krafft, Martin Reber, Roman Krafft, Anna Couturier, Katharina Anna Zweig:
Crucial Challenges in Large-Scale Black Box Analyses. BIAS 2021: 143-155 - Mykola Makhortykh, Aleksandra Urman, Roberto Ulloa:
Detecting Race and Gender Bias in Visual Representation of AI on Web Search Engines. BIAS 2021: 36-50 - Joanna Misztal-Radecka, Bipin Indurkhya:
When Is a Recommendation Model Wrong? A Model-Agnostic Tree-Based Approach to Detecting Biases in Recommendations. BIAS 2021: 92-105 - Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello, Gian Antonio Susto:
Incentives for Item Duplication Under Fair Ranking Policies. BIAS 2021: 64-77 - Luisa Simões, Vaibhav Shah, João Silva, Nelson Rodrigues, Nuno Leite, Nuno Lopes:
New Performance Metrics for Offline Content-Based TV Recommender System. BIAS 2021: 156-169 - Ludovico Boratto, Stefano Faralli, Mirko Marras, Giovanni Stilo:
Advances in Bias and Fairness in Information Retrieval - Second International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2021, Lucca, Italy, April 1, 2021, Proceedings. Communications in Computer and Information Science 1418, Springer 2021, ISBN 978-3-030-78817-9 [contents] - 2020
- Xiao Bai, Berkant Barla Cambazoglu, Francesco Gullo, Amin Mantrach, Fabrizio Silvestri:
Improving News Personalization Through Search Logs. BIAS 2020: 152-166 - Mohammad Aliannejadi, Fabio Crestani:
Venue Suggestion Using Social-Centric Scores. BIAS 2020: 127-142 - Sihem Amer-Yahia, Anh Tho Le, Eric Simon:
Data Pipelines for Personalized Exploration of Rated Datasets. BIAS 2020: 72-78 - Alessandro Celi, Alejandro Piad, Jósval Díaz Blanco, Romina Eramo:
Analyzing the Interaction of Users with News Articles to Create Personalization Services. BIAS 2020: 167-180 - Seyed Amin Mirlohi Falavarjani, Hawre Hosseini, Ebrahim Bagheri:
The Impact of Foursquare Checkins on Users' Emotions on Twitter. BIAS 2020: 143-151 - Emma J. Gerritse, Arjen P. de Vries:
Effect of Debiasing on Information Retrieval. BIAS 2020: 35-42 - Giannis Konstantakis, Gianins Promponas, Manthos Dretakis, Panagiotis Papadakos:
[inline-graphic not available: see fulltext]: Exploring the Bias of Web Domains Through the Eyes of Users. BIAS 2020: 66-71 - Tobias D. Krafft, Marc P. Hauer, Katharina Anna Zweig:
Why Do We Need to Be Bots? What Prevents Society from Detecting Biases in Recommendation Systems. BIAS 2020: 27-34
