On the orthogonality of bias and utility in ad hoc retrieval

Amin Bigdeli, Negar Arabzadeh, Shirin Seyedsalehi, Morteza Zihayat, Ebrahim Bagheri
January 2021

Abstract

This paper examines the orthogonality of bias and utility in ad hoc retrieval systems, contributing to fair and effective information retrieval.

Type
Conference paper
Publication
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval

This work investigates the relationship between bias and utility in information retrieval systems.

Information Retrieval Bias Analysis Utility Optimization Fair Retrieval Ad Hoc Retrieval
Shirin Seyedsalehi
PhD Student (Alumni)

Shirin Seyedsalehi is a former PhD student and alumna of the Human-Centered Machine Intelligence Lab.

Morteza Zihayat
Morteza Zihayat
Principal Investigator

Dr. Morteza Zihayat is a Canada Research Chair (CRC) in Human-Centered AI and Associate Professor at Toronto Metropolitan University, Faculty of Engineering and Architectural Science. He also holds appointments as Adjunct Associate Professor at the University of Waterloo (Management Sciences) and IBM Faculty Fellow at IBM Centre for Advanced Studies. He is the Director of the Human-Centered Machine Intelligence Lab.