Introduction to the Special Issue on Trustworthy Recommender Systems

This editorial introduces the Special Issue on Trustworthy Recommender Systems , hosted by the ACM Transactions on Recommender Systems in 2024. We provide an overview on the multifaceted aspects of trustworthiness and point to recent regulations that underline the importance of the topic, also beyond technical perspectives. Subsequently, we present the nine articles constituting the special issue: one survey that reviews over 400 papers, categorizing them according to five trustworthiness dimensions, and eight research articles . We categorize and introduce the latter according to the major trustworthiness dimensions they address, specifically into privacy/security , transparency/explainability , and bias/fairness . We provide a summary of their main contributions and end with a brief personal statement about envisioned challenges ahead.

Authors

Institutions

Publication Details

Journal
ACM Transactions on Recommender Systems
Published
2024-11-27
DOI
https://doi.org/10.1145/3702249
Citations
2
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
1.56
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Introduction to the Special Issue on Trustworthy Recommender Systems

Yashar Deldjoo, Pablo Castells, Markus Schedl, Emine Yilmaz
2 citations
ACM Transactions on Recommender Systems
Recommender Systems and Techniques
1.56
article

Introduction to the Special Issue on Trustworthy Recommender Systems

Yashar Deldjoo, Pablo Castells, Markus Schedl, Emine Yilmaz
article en
2 citations

Abstract

This editorial introduces the Special Issue on Trustworthy Recommender Systems , hosted by the ACM Transactions on Recommender Systems in 2024. We provide an overview on the multifaceted aspects of trustworthiness and point to recent regulations that underline the importance of the topic, also beyond technical perspectives. Subsequently, we present the nine articles constituting the special issue: one survey that reviews over 400 papers, categorizing them according to five trustworthiness dimensions, and eight research articles . We categorize and introduce the latter according to the major trustworthiness dimensions they address, specifically into privacy/security , transparency/explainability , and bias/fairness . We provide a summary of their main contributions and end with a brief personal statement about envisioned challenges ahead.

ACM Transactions on Recommender SystemsVol. 3(2)
Johannes Kepler University of Linz (AT), Amazon (United States) (US), University College London (GB), Universidad Autónoma de Madrid (ES), Polytechnic University of Bari (IT)
Peace, Justice and strong institutions
Openalex Percentile: Top 12%
Recommender Systems and Techniques
1.56
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Introduction to the Special Issue on Trustworthy Recommender Systems — Yashar Deldjoo, Pablo Castells, et al. · ACM Transactions on Recommender Systems (2024) | TGRS Research Map | TGRS