Identifying expertise through semantic modeling: A modified BBPSO algorithm for the reviewer assignment problem

Yang, Chen; Liu, Tingting; Yi, Wenjie; Chen, Xiaohong; Niu, Ben

doi:10.1016/j.asoc.2020.106483

Cited by 11 publications

(11 citation statements)

References 42 publications

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“…As many researchers agree (Wang et al, 2008;Xu et al, 2010;Kou et al, 2015a;Peng et al, 2017;Duan et al, 2019;Yang et al, 2020), proposed approaches for stages 2 and 3 are divided into two main categories: i) the information retrieval-based reviewer assignment problem (IRRAP) and (ii) the optimization-based reviewer assignment problem (ORAP). The distribution of 103 publications into two main categories is presented in Figure 5.…”

Section: Stages Of Reviewer Assignment Process and Related Methodolog...mentioning

confidence: 99%

“…The model captures the interchangeability of both words and texts with the Dirichlet distribution, allowing for a cohesive test data generation procedure. It is seen that LDA is widely applied to extract topics representation from the reviewer's published studies and the submitted proposals (Mimno & Mccallum, 2007;Tang et al, 2010;Tang et al, 2012;Charlin & Zemel, 2013;Liu et al, 2014;Xu & Zuo, 2016;Peng et al, 2017;Yan et al, 2017;Nguyen et al, 2018;Medakene et al, 2019;Pradhan et al, 2020;Yang et al, 2020;Patil & Mahalle, 2021;Tan et al, 2021;Hoang et al, 2021).…”

Section: Probabilistic Latent Semantic Analysis (Plsa)mentioning

confidence: 99%

“…To maximize the sum of similarity scores, most researchers have structured the RAP as an integer linear programming (ILP) formulation (Guerv´os & Valdivieso, 2004;Janak et al, 2006;Li et al, 2008;Taylor et al, 2008;Conry et al, 2009;Xu et al, 2010;Chen et al, 2012;Charlin et al, 2012;Charlin & Zemel, 2013;Silva et al, 2014;Li & Hou, 2016;Ogunleyu et al, 2017;Jin et al, 2018b;Yang et al, 2020;Kat, 2021). Some researchers proposed a formulation known as mixed integer programming (MIP), which includes an additional set of continuous variables into the objective function for constraint relaxation.…”

Section: Maximizing Cumulative Sum Of Similarity Scoresmentioning

confidence: 99%

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Reviewer Assignment Problem: A Systematic Review of the Literature

Meltem¹,

Yanık

Amasyalı

2023

jair

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Appropriate reviewer assignment significantly impacts the quality of proposal evaluation, as accurate and fair reviews are contingent on their assignment to relevant reviewers. The crucial task of assigning reviewers to submitted proposals is the starting point of the review process and is also known as the reviewer assignment problem (RAP). Due to the obvious restrictions of manual assignment, journal editors, conference organizers, and grant managers demand automatic reviewer assignment approaches. Many studies have proposed assignment solutions in response to the demand for automated procedures since 1992. The primary objective of this survey paper is to provide scholars and practitioners with a comprehensive overview of available research on the RAP. To achieve this goal, this article presents an in-depth systematic review of 103 publications in the field of reviewer assignment published in the past three decades and available in the Web of Science, Scopus, ScienceDirect, Google Scholar, and Semantic Scholar databases. This review paper classified and discussed the RAP approaches into two broad categories and numerous subcategories based on their underlying techniques. Furthermore, potential future research directions for each category are presented. This survey shows that the research on the RAP is becoming more significant and that more effort is required to develop new approaches and a framework.

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Section: Stages Of Reviewer Assignment Process and Related Methodolog...mentioning

confidence: 99%

Section: Probabilistic Latent Semantic Analysis (Plsa)mentioning

confidence: 99%

Section: Maximizing Cumulative Sum Of Similarity Scoresmentioning

confidence: 99%

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Reviewer Assignment Problem: A Systematic Review of the Literature

Meltem¹,

Yanık

Amasyalı

2023

jair

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“…Amongst others we also observe these factors but define them differently. Yang et al [22] utilise LDA to represent manuscripts as well as past publications of reviewer candidates. They then use a discrete optimisation model which focuses on expertise to assign reviewers to all manuscripts.…”

Section: Reviewer Set Recommendationmentioning

confidence: 99%

“…Numerous works [3,6,8,9,14,17,22,24] tackle the reviewer assignment problem in different ways, with slightly different definitions for the suitability of reviewers. While expertise of a reviewer with the topic of the manuscript [3,6,8,9,14,22,24] has been dominating in existing work, other features like authority [8,14], research interest [8] and diversity [6,14,17] were considered in some existing work, but not in a holistic way. Additionally, these aspects were defined heterogeneously in present works.…”

Section: Introductionmentioning

confidence: 99%

RevASIDE: Assignment of Suitable Reviewer Sets for Publications from Fixed Candidate Pools

Kreutz¹,

Schenkel²

2021

Preprint

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Scientific publishing heavily relies on the assessment of quality of submitted manuscripts by peer reviewers. Assigning a set of matching reviewers to a submission is a highly complex task which can be performed only by domain experts. We introduce RevASIDE, a reviewer recommendation system that assigns suitable sets of complementing reviewers from a predefined candidate pool without requiring manually defined reviewer profiles. Here, suitability includes not only reviewers' expertise, but also their authority in the target domain, their diversity in their areas of expertise and experience, and their interest in the topics of the manuscript. We present three new data sets for the expert search and reviewer set assignment tasks and compare the usefulness of simple text similarity methods to document embeddings for expert search. Furthermore, an quantitative evaluation demonstrates significantly better results in reviewer set assignment compared to baselines. A qualitative evaluation also shows their superior perceived quality.

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Literature Review

Protasiewicz

2023

Knowledge Recommendation Systems With Machine Intelligence Algorithms

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Identifying expertise through semantic modeling: A modified BBPSO algorithm for the reviewer assignment problem

Cited by 11 publications

References 42 publications

Reviewer Assignment Problem: A Systematic Review of the Literature

Reviewer Assignment Problem: A Systematic Review of the Literature

RevASIDE: Assignment of Suitable Reviewer Sets for Publications from Fixed Candidate Pools

Literature Review

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