Group-to-group reviewer assignment problem

Wang, Fan; Zhou, Shaorui; Shi, Ning

doi:10.1016/j.cor.2012.08.005

Cited by 21 publications

(12 citation statements)

References 14 publications

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“…An example is given in Figure 1(a), where reviewer r1, whose research interest is mainly in spatial databases, receives 3 related papers to review but another reviewer (r2) receives no paper by this assignment. Another line of work [6,7,14,18,21,27,29] regard RAP as an assignment problem subject to a maximum workload per reviewer and the number of required reviews per paper. These assignment-based RAPs aim at finding the best assignment (i.e., an assignment objective is optimized) subject to the aforementioned constraints.…”

Section: Previous Workmentioning

confidence: 99%

Weighted Coverage based Reviewer Assignment

Kou

Hou

Mamoulis

et al. 2015

Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

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Peer reviewing is a standard process for assessing the quality of submissions at academic conferences and journals. A very important task in this process is the assignment of reviewers to papers. However, achieving an appropriate assignment is not easy, because all reviewers should have similar load and the subjects of the assigned papers should be consistent with the reviewers' expertise. In this paper, we propose a generalized framework for fair reviewer assignment. We first extract the domain knowledge from the reviewers' published papers and model this knowledge as a set of topics. Then, we perform a group assignment of reviewers to papers, which is a generalization of the classic Reviewer Assignment Problem (RAP), considering the relevance of the papers to topics as weights. We study a special case of the problem, where reviewers are to be found for just one paper (Journal Assignment Problem) and propose an exact algorithm which is fast in practice, as opposed to brute-force solutions. For the general case of having to assign multiple papers, which is too hard to be solved exactly, we propose a greedy algorithm that achieves a 1/2-approximation ratio compared to the exact solution. This is a great improvement compared to the 1/3-approximation solution proposed in previous work for the simpler coverage-based reviewer assignment problem, where there are no weights on topics. We theoretically prove the approximation bound of our solution and experimentally show that it is superior to the current state-of-the-art.

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Section: Previous Workmentioning

confidence: 99%

Weighted Coverage based Reviewer Assignment

Kou

Hou

Mamoulis

et al. 2015

Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

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“…The influence between stringent or lenient reviewers is balanced via a cross-assignment paradigm. Similarly, the matching degree between reviewers and submissions and manuscript and reviewer diversities were consolidated in a multi-objective mixed integer programming problem to assign a group of reviewer candidates for a group of submissions in Wang et al [26]. A two-phase stochastic-biased greedy algorithm is utilised to analyse this multi-objective, mixed integer programming problem.…”

Section: Related Workmentioning

confidence: 99%

Author–Subject–Topic model for reviewer recommendation

Jin

Geng

Mou

et al. 2018

Journal of Information Science

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Interdisciplinary studies are becoming increasingly popular, and research domains of many experts are becoming diverse. This phenomenon brings difficulty in recommending experts to review interdisciplinary submissions. In this study, an Author–Subject–Topic (AST) model is proposed with two versions. In the model, reviewers’ subject information is embedded to analyse topic distributions of submissions and reviewers’ publications. The major difference between the AST and Author–Topic models lies in the introduction of a ‘Subject’ layer, which supervises the generation of hierarchical topics and allows sharing of subjects among authors. To evaluate the performance of the AST model, papers in Information System and Management (a typical interdisciplinary domain) in a famous Chinese academic library are investigated. Comparative experiments are conducted, which show the effectiveness of the AST model in topic distribution analysis and reviewer recommendation for interdisciplinary studies.

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“…Although many different versions of assignment problems have been defined and explored, there are only a very few problems remotely related to M W T M problem reported in the literature, such as [7], and [8]. Similar to M W T M , both of these problems introduce different kinds of set constraints on the vertices of a bipartite graph, and they have both been shown to be NP-hard.…”

Section: Introductionmentioning

confidence: 99%

“…Similar to M W T M , both of these problems introduce different kinds of set constraints on the vertices of a bipartite graph, and they have both been shown to be NP-hard. Therefore, heuristic solutions have been proposed, namely a greedy heuristic for [7], and a genetic algorithm based solution for [8], and these solutions have been shown to be quite effective.…”

Section: Introductionmentioning

confidence: 99%

Task assignment in tree-like hierarchical structures

2016

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Most large organizations, such as corporations, are hierarchical organizations. In hierarchical organizations each entity in the organization, except the root entity, is a sub-part of another entity. In this paper we study the task assignment problem to the entities of tree-like hierarchical organizations. The inherent tree structure introduces an interesting and challenging constraint to the standard assignment problem. When a task is assigned to an entity in a hierarchical organization, the whole entity, including its sub-entities, is responsible from the execution of that particular task. In other words, if an entity has been assigned to a task, neither its descendants nor its ancestors can be assigned to a task. Sub-entities cannot be assigned as they have an ancestor already occupied. Ancestor entities cannot be assigned since one of their sub-entities has already been employed in an assignment. In the paper, we formally introduce this new version of the assignment problem called Maximum Weight Tree Matching (M W T M ), and show its NP-hardness. We also propose an effective heuristic solution based on an iterative LP-relaxation to it.

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Group-to-group reviewer assignment problem

Cited by 21 publications

References 14 publications

Weighted Coverage based Reviewer Assignment

Weighted Coverage based Reviewer Assignment

Author–Subject–Topic model for reviewer recommendation

Task assignment in tree-like hierarchical structures

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