How to Choose Appropriate Experts for Peer Review: An Intelligent Recommendation Method in a Big Data Context | Zendy

Duanduan Liu | Zendy; Wei Xu | Zendy; Wei Du | Zendy; Fuyin Wang | Zendy

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How to Choose Appropriate Experts for Peer Review: An Intelligent Recommendation Method in a Big Data Context

Author(s) -

Duanduan Liu,

Wei Xu,

Wei Du,

Fuyin Wang

Publication year - 2015

Publication title -

data science journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.358

H-Index - 21

ISSN - 1683-1470

DOI - 10.5334/dsj-2015-016

Subject(s) - computer science , big data , set (abstract data type) , data science , context (archaeology) , the internet , recommender system , data set , collaborative filtering , information retrieval , peer to peer , world wide web , data mining , artificial intelligence , paleontology , biology , programming language

The rapid development of the internet has led to the accumulation of massive amounts of data, and thus we find ourselves entering the age of big data. Obtaining useful information from these big data is a crucial issue. The aim of this article is to solve the problem of recommending experts to provide peer reviews for universities and other scientific research institutions. Our proposed recommendation method has two stages. An information filtering method is first offered to identify proper experts as a candidate set. Then, an aggregation model with various constraints is suggested to recommend appropriate experts for each applicant. The proposed method has been implemented in an online research community, and the results exhibit that the proposed method is more effective than existing ones

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