A New Approach to Measuring Distances in Dense Graphs

Almulhim, F, Thwaites, PA orcid.org/0000-0001-9700-2245 and Taylor, CC orcid.org/0000-0003-0181-1094 (2019) A New Approach to Measuring Distances in Dense Graphs. In: Machine Learning, Optimization and Data Science. Lecture Notes in Computer Science . Springer, Cham , pp. 204-216. ISBN 978-3-030-13708-3

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Copyright, Publisher and Additional Information: © Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of a chapter published in Lecture Notes in Computer Science volume 11331. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-13709-0_17.
Keywords: Network; Adjacency matrix; K-means clustering; Hierarchical clustering; Modularity function
Dates:
  • Published: 14 February 2019
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 13 May 2019 09:35
Last Modified: 14 Feb 2020 01:39
Status: Published
Publisher: Springer, Cham
Series Name: Lecture Notes in Computer Science

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