Constrained multi-aspect expertise matching for committee review assignment

Maryam Karimzadehgan, Cheng Xiang Zhai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. Most previous works have set the problem up as using a paper as a query to independently "retrieve" a set of reviewers that should review the paper. A more appropriate formulation of the problem would be to simultaneously optimize the assignments of all the papers to an entire committee of reviewers under constraints such as the review quota. In this paper, we solve the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using an existing data set shows that the proposed algorithm is effective for committee review assignments based on multi-aspect expertise matching.

Original languageEnglish (US)
Title of host publicationACM 18th International Conference on Information and Knowledge Management, CIKM 2009
Pages1697-1700
Number of pages4
DOIs
StatePublished - 2009
EventACM 18th International Conference on Information and Knowledge Management, CIKM 2009 - Hong Kong, China
Duration: Nov 2 2009Nov 6 2009

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

OtherACM 18th International Conference on Information and Knowledge Management, CIKM 2009
Country/TerritoryChina
CityHong Kong
Period11/2/0911/6/09

Keywords

  • Algorithms
  • Combinatorial optimization
  • Review assignment
  • Topic models

ASJC Scopus subject areas

  • General Decision Sciences
  • General Business, Management and Accounting

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