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Paper Matching with Local Fairness Constraints
- Source :
- KDD
- Publication Year :
- 2019
- Publisher :
- ACM, 2019.
-
Abstract
- Automatically matching reviewers to papers is a crucial step of the peer review process for venues receiving thousands of submissions. Unfortunately, common paper matching algorithms often construct matchings suffering from two critical problems: (1) the group of reviewers assigned to a paper do not collectively possess sufficient expertise, and (2) reviewer workloads are highly skewed. In this paper, we propose a novel local fairness formulation of paper matching that directly addresses both of these issues. Since optimizing our formulation is not always tractable, we introduce two new algorithms, FairIR and FairFlow, for computing fair matchings that approximately optimize the new formulation. FairIR solves a relaxation of the local fairness formulation and then employs a rounding technique to construct a valid matching that provably maximizes the objective and only compromises on fairness with respect to reviewer loads and papers by a small constant. In contrast, FairFlow is not provably guaranteed to produce fair matchings, however it can be 2x as efficient as FairIR and an order of magnitude faster than matching algorithms that directly optimize for fairness. Empirically, we demonstrate that both FairIR and FairFlow improve fairness over standard matching algorithms on real conference data. Moreover, in comparison to state-of-the-art matching algorithms that optimize for fairness only, FairIR achieves higher objective scores, FairFlow achieves competitive fairness, and both are capable of more evenly allocating reviewers.<br />Appears at KDD 2019 Research Track, 20 pages
- Subjects :
- FOS: Computer and information sciences
Matching (statistics)
Mathematical optimization
Computer science
Relaxation (iterative method)
Approximation algorithm
Computer Science - Digital Libraries
02 engineering and technology
Construct (python library)
Flow network
Constant (computer programming)
020204 information systems
Computer Science - Data Structures and Algorithms
0202 electrical engineering, electronic engineering, information engineering
Data Structures and Algorithms (cs.DS)
Digital Libraries (cs.DL)
020201 artificial intelligence & image processing
Integer programming
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
- Accession number :
- edsair.doi.dedup.....a05e159cbbeb2f97db19a6928ebae92d