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Interplay between upsampling and regularization for provider fairness in recommender systems

User modeling and user-adapted interaction, 2021-07, Vol.31 (3), p.421-455

2021

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Group Recommender Systems: An Introduction

Second edition., 2023

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Advances in Bias and Fairness in Information Retrieval: 4th International Workshop, BIAS 2023, Dublin, Ireland, April 2, 2023, Revised Selected Papers

1, 2023

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Advances in Bias and Fairness in Information Retrieval: Third International Workshop, BIAS 2022, Stavanger, Norway, April 10, 2022, Revised Selected Papers

1, 2022

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Modeling real-time data and contextual information from workouts in eCoaching platforms to predict users’ sharing behavior on Facebook

User modeling and user-adapted interaction, 2020-07, Vol.30 (3), p.395-411

2020

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Characterizing user behavior in journey planning

Computing, 2020-05, Vol.102 (5), p.1245-1258

2020

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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

1st Edition 2021, 2021

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Bias and Social Aspects in Search and Recommendation: First International Workshop, BIAS 2020, Lisbon, Portugal, April 14, Proceedings

1st ed. 2020., 2020

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Connecting user and item perspectives in popularity debiasing for collaborative recommendation

Information processing & management, 2021-01, Vol.58 (1), p.102387, Article 102387

2021

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Disparate Impact in Item Recommendation: A Case of Geographic Imbalance

Advances in Information Retrieval, p.190-206

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A multi-biometric system for continuous student authentication in e-learning platforms

Pattern recognition letters, 2018-10, Vol.113, p.83-92

2018

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From the Beatles to Billie Eilish: Connecting Provider Representativeness and Exposure in Session-Based Recommender Systems

Advances in Information Retrieval, p.201-208

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Introduction to the Special Issue on Human–Computer Interaction and the Social Web

Future internet, 2016-09, Vol.8 (3), p.43

2016

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On the negative impact of social influence in recommender systems: A study of bribery in collaborative hybrid algorithms

Information processing & management, 2020-03, Vol.57 (2), p.102058, Article 102058

2020

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Group Recommender Systems: An Introduction

1st ed. 2018 edition., 2018

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Robust reputation independence in ranking systems for multiple sensitive attributes

Machine learning, 2022-10, Vol.111 (10), p.3769-3796

2022

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Data-driven user behavioral modeling: from real-world behavior to knowledge, algorithms, and systems: Special issue introduction

Journal of intelligent information systems, 2020-02, Vol.54 (1), p.1-4

2020

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Data-driven user behavioral modeling: from real-world behavior to knowledge, algorithms, and systems

Journal of intelligent information systems, 2020-02, Vol.54 (1), p.1-4

2020

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Group Recommender Systems: An Introduction

2nd ed. 2024

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The rating prediction task in a group recommender system that automatically detects groups: architectures, algorithms, and performance evaluation

Journal of intelligent information systems, 2015-10, Vol.45 (2), p.221-245

2015

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Provider fairness across continents in collaborative recommender systems

Information processing & management, 2022-01, Vol.59 (1), p.102719, Article 102719

2022

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Group Recommender Systems: State of the Art, Emerging Aspects and Techniques, and Research Challenges

Advances in Information Retrieval, p.889-892

Boratto, Ludovico

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Advances in computer-human interaction for recommender systems (AdCHIReS)

International journal of human-computer studies, 2019-01, Vol.121, p.1-3

2019

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Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations

International journal of artificial intelligence in education, 2022-09, Vol.32 (3), p.636-684

2022

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Investigating the role of the rating prediction task in granularity-based group recommender systems and big data scenarios

Information sciences, 2017-02, Vol.378, p.424-443

2017

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Interplay between upsampling and regularization for provider fairness in recommender systems

Group Recommender Systems: An Introduction

Advances in Bias and Fairness in Information Retrieval: 4th International Workshop, BIAS 2023, Dublin, Ireland, April 2, 2023, Revised Selected Papers

Advances in Bias and Fairness in Information Retrieval: Third International Workshop, BIAS 2022, Stavanger, Norway, April 10, 2022, Revised Selected Papers

Modeling real-time data and contextual information from workouts in eCoaching platforms to predict users’ sharing behavior on Facebook

Characterizing user behavior in journey planning

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

Bias and Social Aspects in Search and Recommendation: First International Workshop, BIAS 2020, Lisbon, Portugal, April 14, Proceedings

Connecting user and item perspectives in popularity debiasing for collaborative recommendation

Disparate Impact in Item Recommendation: A Case of Geographic Imbalance

A multi-biometric system for continuous student authentication in e-learning platforms

From the Beatles to Billie Eilish: Connecting Provider Representativeness and Exposure in Session-Based Recommender Systems

Introduction to the Special Issue on Human–Computer Interaction and the Social Web

On the negative impact of social influence in recommender systems: A study of bribery in collaborative hybrid algorithms

Group Recommender Systems: An Introduction

Robust reputation independence in ranking systems for multiple sensitive attributes

Data-driven user behavioral modeling: from real-world behavior to knowledge, algorithms, and systems: Special issue introduction

Data-driven user behavioral modeling: from real-world behavior to knowledge, algorithms, and systems

Group Recommender Systems: An Introduction

The rating prediction task in a group recommender system that automatically detects groups: architectures, algorithms, and performance evaluation

Provider fairness across continents in collaborative recommender systems

Group Recommender Systems: State of the Art, Emerging Aspects and Techniques, and Research Challenges

Advances in computer-human interaction for recommender systems (AdCHIReS)

Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations

Investigating the role of the rating prediction task in granularity-based group recommender systems and big data scenarios

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