Weak ties based recommendation for interdisciplinary research collaboration

Won Kyung Lee; So Young Sohn

doi:10.1145/3110025.3120990

Weak ties based recommendation for interdisciplinary research collaboration

Won Kyung Lee, So Young Sohn

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
Editors	Jana Diesner, Elena Ferrari, Guandong Xu
Publisher	Association for Computing Machinery, Inc
Pages	1199-1200
Number of pages	2
ISBN (Electronic)	9781450349932
DOIs	https://doi.org/10.1145/3110025.3120990
Publication status	Published - 2017 Jul 31
Event	9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 - Sydney, Australia Duration: 2017 Jul 31 → 2017 Aug 3

Publication series

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

Other

Other	9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
Country/Territory	Australia
City	Sydney
Period	17/7/31 → 17/8/3

Bibliographical note

Publisher Copyright:
© 2017 Association for Computing Machinery.

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Information Systems

Access to Document

10.1145/3110025.3120990

Cite this

Lee, W. K., & Sohn, S. Y. (2017). Weak ties based recommendation for interdisciplinary research collaboration. In J. Diesner, E. Ferrari, & G. Xu (Eds.), Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 (pp. 1199-1200). (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017). Association for Computing Machinery, Inc. https://doi.org/10.1145/3110025.3120990

Lee, Won Kyung ; Sohn, So Young. / Weak ties based recommendation for interdisciplinary research collaboration. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. editor / Jana Diesner ; Elena Ferrari ; Guandong Xu. Association for Computing Machinery, Inc, 2017. pp. 1199-1200 (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017).

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title = "Weak ties based recommendation for interdisciplinary research collaboration",

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.",

author = "Lee, {Won Kyung} and Sohn, {So Young}",

note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 ; Conference date: 31-07-2017 Through 03-08-2017",

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doi = "10.1145/3110025.3120990",

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Lee, WK & Sohn, SY 2017, Weak ties based recommendation for interdisciplinary research collaboration. in J Diesner, E Ferrari & G Xu (eds), Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, Association for Computing Machinery, Inc, pp. 1199-1200, 9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, Sydney, Australia, 17/7/31. https://doi.org/10.1145/3110025.3120990

Weak ties based recommendation for interdisciplinary research collaboration. / Lee, Won Kyung; Sohn, So Young.
Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. ed. / Jana Diesner; Elena Ferrari; Guandong Xu. Association for Computing Machinery, Inc, 2017. p. 1199-1200 (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Lee WK, Sohn SY. Weak ties based recommendation for interdisciplinary research collaboration. In Diesner J, Ferrari E, Xu G, editors, Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. Association for Computing Machinery, Inc. 2017. p. 1199-1200. (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017). doi: 10.1145/3110025.3120990

Weak ties based recommendation for interdisciplinary research collaboration

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