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IIRank: co-ranking scientific articles by characterizing their innovativeness and importance

conference contribution
posted on 2017-01-01, 00:00 authored by F Li, Zili ZhangZili Zhang, L Li, X Xu, S He
The dynamic nature of literature networks makes the task of ranking scientific articles hard, hence we present a framework(IIRank) to determine the influence of the proportion of feature pairs in the scientific article on the innovation of the article and to co-rank the scientific article. The model is based on the title, keyword and abstract information extracted from the scientific article, which make it possible to consider the feature pair of the scientific article as the sensors of their innovativeness and importance, and we use the Entropy method to judge the importance degree of a feature pair, the greater the importance degree, the greater the impact on the comprehensive evaluation.

History

Volume

Part F131195

Pagination

247-248

Location

Chongqing, China

Start date

2017-09-22

End date

2017-09-23

ISBN-13

9781450353526

Language

eng

Publication classification

E Conference publication, E1.1 Full written paper - refereed

Copyright notice

2017, Copyright held by the owner/author(s)

Editor/Contributor(s)

Unknown

Title of proceedings

ChineseCSCW2017 : Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing

Event

Computer supported cooperative work and social computing. Chinese conference (12th : 2017 : Chongqing, China)

Publisher

The Association for Computing Machinery

Place of publication

New York, N.Y.

Series

ACM Digital Library