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An axiomatic role similarity measure based on graph topology
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Yu, Weiren, Iranmanesh, Sima, Haldar, Aparajita, Zhang, Maoyin and Ferhatosmanoglu, Hakan (2020) An axiomatic role similarity measure based on graph topology. In: SFDI 2020 : LSGDA 2020. Published in: Software Foundations for Data Interoperability and Large Scale Graph Data Analytics, 1281 pp. 33-48. ISBN 9783030611323. doi:10.1007/978-3-030-61133-0_3 ISSN 1865-0929.
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WRAP-Axiomatic-role-similarity-measure-graph-topology-2020.pdf - Accepted Version - Requires a PDF viewer. Download (1244Kb) | Preview |
Official URL: http://dx.doi.org/10.1007/978-3-030-61133-0_3
Abstract
RoleSim and SimRank are popular graph-theoretic similarity measures with many applications in, e.g., web search, collaborative filtering, and sociometry. While RoleSim addresses the automorphic (role) equivalence of pairwise similarity which SimRank lacks, it ignores the neighboring similarity information out of the automorphically equivalent set. Consequently, two pairs of nodes, which are not automorphically equivalent by nature, cannot be well distinguished by RoleSim if the averages of their neighboring similarities over the automorphically equivalent set are the same.
Item Type: | Conference Item (Paper) | ||||
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Subjects: | H Social Sciences > HM Sociology Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Library of Congress Subject Headings (LCSH): | Graph theory, Data mining, Web search engines , Sociometry | ||||
Series Name: | Communications in Computer and Information Science | ||||
Journal or Publication Title: | Software Foundations for Data Interoperability and Large Scale Graph Data Analytics | ||||
Publisher: | Springer | ||||
ISBN: | 9783030611323 | ||||
ISSN: | 1865-0929 | ||||
Book Title: | Software Foundations for Data Interoperability and Large Scale Graph Data Analytics | ||||
Official Date: | 6 November 2020 | ||||
Dates: |
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Volume: | 1281 | ||||
Page Range: | pp. 33-48 | ||||
DOI: | 10.1007/978-3-030-61133-0_3 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Reuse Statement (publisher, data, author rights): | This is a post-peer-review, pre-copyedit version of an article published in Software Foundations for Data Interoperability and Large Scale Graph Data Analytics. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-61133-0_3 | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 25 June 2021 | ||||
Date of first compliant Open Access: | 6 November 2022 | ||||
Conference Paper Type: | Paper | ||||
Title of Event: | SFDI 2020 : LSGDA 2020 | ||||
Type of Event: | Conference |
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