Recommendation for Cross-Disciplinary Collaboration Based on Potential Research Field Discovery

Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Qun Jin*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, cross-disciplinary scientific collaboration has been proved to be promising for both research practice and innovation. Lots of efforts have been spent in collaboration recommendation. However, the cross-disciplinary information is hidden in tons of publications, and the relationships between different fields are complicated, which make it challengeable recommending cross-disciplinary collaboration for a specific researcher. In this paper, a novel cross-disciplinary collaboration recommendation method (CDCR) that unearths the common cross-disciplinary collaboration patterns and historical scientific field preferences of authors is proposed to recommend potential cross-disciplinary research collaboration. In CDCR, a research field discovery algorithm is designed to classify scientific topics obtained from the publications into the correct field automatically. Then, the collaborative patterns are studied through analyzing the composition fields and the corresponding percentage of all publications. Furthermore, we investigate the common correlation of different research fields. Based on the common correlation and the researcher's specific pattern, the most valuable fields will be listed by CDCR. The effectiveness of our approach is evaluated based on a real academic dataset.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages349-354
Number of pages6
ISBN (Electronic)9781538610725
DOIs
Publication statusPublished - 2017 Sep 6
Event5th International Conference on Advanced Cloud and Big Data, CBD 2017 - Shanghai, China
Duration: 2017 Aug 132017 Aug 16

Publication series

NameProceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017

Other

Other5th International Conference on Advanced Cloud and Big Data, CBD 2017
Country/TerritoryChina
CityShanghai
Period17/8/1317/8/16

Keywords

  • Cross-disciplinary
  • Data mining
  • Research field discovery
  • Scientific collaboration

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

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