Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval
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Published By Springer International Publishing

9783030788179, 9783030788186

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New Performance Metrics for Offline Content-Based TV Recommender System

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_14 ◽

2021 ◽

pp. 156-169

Author(s):

Luisa Simões ◽

Vaibhav Shah ◽

João Silva ◽

Nelson Rodrigues ◽

Nuno Leite ◽

...

Keyword(s):

Recommender System ◽

Performance Metrics

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Media Bias Everywhere? A Vision for Dealing with the Manipulation of Public Opinion

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_2 ◽

2021 ◽

pp. 9-13

Author(s):

Michael Färber ◽

Frederic Bartscherer

Keyword(s):

Public Opinion ◽

Media Bias

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Towards Fairness-Aware Ranking by Defining Latent Groups Using Inferred Features

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_1 ◽

2021 ◽

pp. 1-8

Author(s):

Yunhe Feng ◽

Daniel Saelid ◽

Ke Li ◽

Ruoyuan Gao ◽

Chirag Shah

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An Information-Theoretic Measure for Enabling Category Exemptions with an Application to Filter Bubbles

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_11 ◽

2021 ◽

pp. 117-129

Author(s):

Chenyu Jiang ◽

Bowen Wu ◽

Sanghamitra Dutta ◽

Pulkit Grover

Keyword(s):

Information Theoretic ◽

Filter Bubbles

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When Is a Recommendation Model Wrong? A Model-Agnostic Tree-Based Approach to Detecting Biases in Recommendations

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_9 ◽

2021 ◽

pp. 92-105

Author(s):

Joanna Misztal-Radecka ◽

Bipin Indurkhya

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Perception-Aware Bias Detection for Query Suggestions

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_12 ◽

2021 ◽

pp. 130-142

Author(s):

Fabian Haak ◽

Philipp Schaer

Keyword(s):

Bias Detection ◽

Query Suggestions

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Crucial Challenges in Large-Scale Black Box Analyses

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_13 ◽

2021 ◽

pp. 143-155

Author(s):

Tobias D. Krafft ◽

Martin Reber ◽

Roman Krafft ◽

Anna Coutrier ◽

Katharina A. Zweig

Keyword(s):

Large Scale ◽

Black Box

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Examining Video Recommendation Bias on YouTube

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_10 ◽

2021 ◽

pp. 106-116

Author(s):

Baris Kirdemir ◽

Joseph Kready ◽

Esther Mead ◽

Muhammad Nihal Hussain ◽

Nitin Agarwal

Keyword(s):

Video Recommendation

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Incentives for Item Duplication Under Fair Ranking Policies

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_7 ◽

2021 ◽

pp. 64-77

Author(s):

Giorgio Maria Di Nunzio ◽

Alessandro Fabris ◽

Gianmaria Silvello ◽

Gian Antonio Susto

Keyword(s):

Fair Ranking

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Quantification of the Impact of Popularity Bias in Multi-stakeholder and Time-Aware Environments

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval ◽

10.1007/978-3-030-78818-6_8 ◽

2021 ◽

pp. 78-91

Author(s):

Francisco Guíñez ◽

Javier Ruiz ◽

María Ignacia Sánchez

Keyword(s):

Multi Stakeholder ◽

The Impact ◽

Time Aware

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Communications in Computer and Information Science - Advances in Bias and Fairness in Information RetrievalLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

New Performance Metrics for Offline Content-Based TV Recommender System

Media Bias Everywhere? A Vision for Dealing with the Manipulation of Public Opinion

Towards Fairness-Aware Ranking by Defining Latent Groups Using Inferred Features

An Information-Theoretic Measure for Enabling Category Exemptions with an Application to Filter Bubbles

When Is a Recommendation Model Wrong? A Model-Agnostic Tree-Based Approach to Detecting Biases in Recommendations

Perception-Aware Bias Detection for Query Suggestions

Crucial Challenges in Large-Scale Black Box Analyses

Examining Video Recommendation Bias on YouTube

Incentives for Item Duplication Under Fair Ranking Policies

Quantification of the Impact of Popularity Bias in Multi-stakeholder and Time-Aware Environments

Communications in Computer and Information Science - Advances in Bias and Fairness in Information Retrieval
Latest Publications