How to choose appropriate experts for peer review: An intelligent recommendation method in a big data context

Duanduan Liu; Wei Xu; Wei Du; Fuyin Wang

doi:10.5334/dsj-2015-016

How to choose appropriate experts for peer review: An intelligent recommendation method in a big data context

Duanduan Liu
, Wei Xu
, Wei Du
, Fuyin Wang

Department of Information Systems

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

16 Citations (Scopus)

2 Downloads (CityUHK Scholars)

Abstract

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. © 2015 The Author(s).

Original language	English
Article number	16
Journal	Data Science Journal
Volume	14
DOIs	https://doi.org/10.5334/dsj-2015-016
Publication status	Published - 2015

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This research work was partly supported by National Natural Science Foundation of China (Grant No.71001103, 91224008, 91324015), Humanities and Social Sciences Foundation of the Ministry of Education (No. 14YJA630075), Beijing Natural Science Foundation (No. 9122013), Beijing Nova Program (No. Z131101000413058), and Program for Excellent Talents in Beijing.

Research Keywords

Big data analysis
Experts recommendation
Integration model
Text mining

Publisher's Copyright Statement

This full text is made available under CC-BY 3.0. https://creativecommons.org/licenses/by/3.0/

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title = "How to choose appropriate experts for peer review: An intelligent recommendation method in a big data context",

abstract = "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. {\textcopyright} 2015 The Author(s).",

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note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].",

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doi = "10.5334/dsj-2015-016",

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T2 - An intelligent recommendation method in a big data context

AU - Liu, Duanduan

AU - Xu, Wei

AU - Du, Wei

AU - Wang, Fuyin

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PY - 2015

Y1 - 2015

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AB - 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. © 2015 The Author(s).

KW - Big data analysis

KW - Experts recommendation

KW - Integration model

KW - Text mining

UR - https://www.scopus.com/pages/publications/84974685739

UR - https://www.scopus.com/pages/publications/84974685739#tab=impact

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DO - 10.5334/dsj-2015-016

M3 - RGC 21 - Publication in refereed journal

SN - 1683-1470

VL - 14

JO - Data Science Journal

JF - Data Science Journal

M1 - 16

ER -

How to choose appropriate experts for peer review: An intelligent recommendation method in a big data context

Abstract

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Research Keywords

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