| Vol-2440 urn:nbn:de:0074-2440-0 Copyright © 2019 for the individual papers by the papers' authors. Copyright © 2019 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# RMSE 2019
Workshop on Recommendation in Multi-stakeholder Environments

### Proceedings of the Workshop on Recommendation in Multi-stakeholder Environments
co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019)

### Copenhagen, Denmark, September 20, 2019.

Edited by

### Robin Burke *
Himan Abdollahpouri *
Edward Malthouse **
KP Thai ***
Yongfeng Zhang ****

* University of Colorado Boulder
** Northwestern University
*** Squirrel AI Learning
**** Rutgers, the State University of New Jersey

## Table of Contents

### Session 1: Welcome and Introduction

- RMSE: Workshop on Recommendation in Multi-stakeholder Environments
  Robin Burke, Himan Abdollahpouri, Edward Malthouse, KP Thai, Yongfeng Zhang

### Session 2: Fairness

- Recommender Systems Fairness Evaluation via Generalized Cross Entropy
  Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogin Kouki, Tommaso Di Noia
- Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness
  Himan Abdollahpouri, Robin Burke
- BlurM(or)e: Revisiting Gender Obfuscation in the User-Item Matrix
  Christopher Strucks, Manel Slokom, Martha Larson

### Session 3: Calibration and Bias Disparity

- Bias Disparity in Recommendation Systems
  Virginia Tsintzou, Evaggelia Pitoura, Panayiotis Tsaparas
- Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison
  Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy
- Crank up the Volume: Preference Bias Amplification in Collaborative Recommendation
  Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke
- The Unfairness of Popularity Bias in Recommendation
  Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher

### Session 4: Multi-stakeholder Recommendation

- Joint Optimization of Profit and Relevance for Recommendation Systems in E-commerce
  Raphael Louca, Moumita Bhattacharya, Diane Hu, Liangjie Hong
- A Multistakeholder Recommender Systems Algorithm for Allocating Sponsored Recommendations
  Edward Malthouse, Khadija Ali Vakeel, Yasaman Kamyab Hessary, Robin Burke, Morana Fuduric
- Simple Objectives Work Better
  Joaquin Delgado, Samuel Lind, Carl Radecke, Satish Konijeti

2019-09-13: submitted by Himan Abdollahpouri, metadata incl. bibliographic data published under Creative Commons CC0
2019-09-15: published on CEUR-WS.org |valid HTML5|