Fairness and Transparency in Ranking

Author:

Castillo Carlos1

Affiliation:

1. Universitat Pompeu Fabra, Barcelona, Spain

Abstract

Ranking in Information Retrieval (IR) has been traditionally evaluated from the perspective of the relevance of search engine results to people searching for information, i.e., the extent to which the system provides "the right information, to the right people, in the right way, at the right time." However, people in current IR systems are not only the ones issuing search queries, but increasingly they are also the ones being searched. This raises several new problems in IR that have been addressed in recent research, particularly with respect to fairness/non-discrimination, accountability, and transparency. This is a summary of some these initial developments.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Management Information Systems

Reference30 articles.

1. Equity of Attention

2. Proceedings of Machine Learning Research;Binns R.,2018

3. Learning to rank

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