Proposal reviewer recommendation system based on big data for a national research management institute

被引：13

作者：

Shon, Ho Sun ^{[1
]}

Han, Sang Hun ^{[1
]}

Kim, Kyung Ah ^{[2
]}

Cha, Eun Jong ^{[2
]}

Ryu, Keun Ho ^{[1
]}

机构：

[1] Chungbuk Natl Univ, Database Bioinformat Lab, Cheongju, South Korea

[2] Chungbuk Natl Univ, Dept Biomed Engn, Cheongju, South Korea

来源：

JOURNAL OF INFORMATION SCIENCE | 2017年 / 43卷 / 02期

基金：

新加坡国家研究基金会;

关键词：

Big data; fuzzy weight; keyword search; research proposal; reviewer;

D O I：

10.1177/0165551516644168

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

National research management organizations need to ensure that research proposals are reviewed fairly and efficiently, which requires the selection of suitable reviewers. In particular, reviewing research proposals in a particular area necessitates the selection of a group with the most reasonable standard for recommending an expert in that area. In this study, we develop an automatic matching system that matches a research proposal with a reviewer who can evaluate it most effectively, using keywords with fuzzy weights based on databases in the corresponding field of research. All functions that we developed were based on the MapReduce framework created by Hadoop, which was verified to enhance matching performance and ensure expandability. This enabled us to select suitable researchers from existing research projects, papers and research reviewer databases. Our system can influence the operation of the national research management system and contribute to academic development.

引用

页码：147 / 158

页数：12

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