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A Topical Coverage and Authority Unification Model for Expert Recommendation
Received date: 2016-09-21
Revised date: 2016-11-14
Online published: 2017-01-05
[Purpose/significance] The selection and recommendation of expert play an important role in the process of publications. Due to the remarkable increase in the number of submissions and candidate experts, selecting the proper experts manually for peer reviewer appears its weakness in terms of the accuracy and efficiency. Accordingly, an intelligent algorithm that automatically selects and recommends experts for submissions is of great importance.[Method/process] In this research, the knowledge of each candidate expert and the research content are extracted, which represent several distinct sub-topics. Then, the topical coverage and the authority of reviewer candidates with respect to each submission, which are treated as indispensable evidences for expert recommendation, are deeply exploited. Finally, these two important factors are linearly combined in an integrated model for recommending proper experts, which is named as CAUFER (Coverage and Authority Unification Framework for Expert Recommendation).[Result/conclusion] Different experiments were conducted and the results show that, compared with the Vector Space Model, Language Model and Latent Dirichlet Allocation, the proposed model will effectively grasp the dynamic authority change as well as the different level authority with respect different subtopics.
Key words: expert recommendation; topic coverage; expert authority; authority
Zhao Qian , Geng Qian , Jin Jian , Wei Yu . A Topical Coverage and Authority Unification Model for Expert Recommendation[J]. Library and Information Service, 2017 , 61(1) : 80 -88 . DOI: 10.13266/j.issn.0252-3116.2017.01.010
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