Integer linear programming for Constrained Multi-Aspect Committee Review Assignment

Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle 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 a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching.

► An integer linear programming (ILP) algorithm for automatic assignment of reviews to a committee of reviewers.
► The ILP algorithm is significantly more accurate than a heuristic greedy algorithm.
► The ILP algorithm works both when topics are given and when they are not.
► The ILP algorithm is scalable to handle review assignment for reasonably large conferences.