Measuring unequal knowledge distance by network embedding and multiple relationships

Keye Wu, Lele Kang, Ziyue Xie, Jia Tina Du, Jianjun Sun

Research output: Other contribution to conferenceAbstractpeer-review

Abstract

Knowledge distance, representing the dissimilarity between different knowledge units, has been considered as an important dimension of recombination novelty and technological innovation. Previous measurements merely rely on the citation relationship and ignore their directions and weights. To fill this gap, this study proposes a new measurement which not only captures the unequal citation relationship but also integrates multiple information to depict knowledge distance. The results show that our method can accurately portray the knowledge distance in both scientific areas and technical fields.
Original languageEnglish
Pages1188-1190
Number of pages3
Publication statusPublished - 2023
Event86th Annual Meeting of the Association for Information Science and Technology 2023: asis&t 2023 - Novotel London West, London, United Kingdom
Duration: 27 Oct 202331 Oct 2023
https://www.asist.org/meetings-events/am/am23/
https://asistdl-onlinelibrary-wiley-com.ezproxy.csu.edu.au/toc/23739231/2023/60/1 (Proceedings)

Other

Other86th Annual Meeting of the Association for Information Science and Technology 2023
Abbreviated titleMaking a Difference: Translating Information Research into Practice, Policy, and Action
Country/TerritoryUnited Kingdom
CityLondon
Period27/10/2331/10/23
Internet address

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