Weak ties based recommendation for interdisciplinary research collaboration

Won Kyung Lee, So Young Sohn

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

Abstract

This study investigates recommendations for interdisciplinary research collaboration based on the weak ties theory. Contents-based features are proposed to recommend interdisciplinary collaboration considering that some researchers who have shown a preference for interdisciplinary collaboration could be connected even if they have dissimilar research profiles. Therefore, we inferred the preference of interdisciplinary research collaboration for every researcher, and considered features such as highlighting dissimilar researchers depending on their preferences. The features are designed to have typical similarity measures when the researchers do not prefer interdisciplinary research collaboration. We evaluated our proposed features with the baseline features of patent application datasets and the former methods outperformed the latter methods.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
EditorsJana Diesner, Elena Ferrari, Guandong Xu
PublisherAssociation for Computing Machinery, Inc
Pages1199-1200
Number of pages2
ISBN (Electronic)9781450349932
DOIs
Publication statusPublished - 2017 Jul 31
Event9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 - Sydney, Australia
Duration: 2017 Jul 312017 Aug 3

Publication series

NameProceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017

Other

Other9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
CountryAustralia
CitySydney
Period17/7/3117/8/3

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (2016R1A2A1A05005270).

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

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