Visually Explaining Publication Ranks in Citation-based Literature Search with PURE Suggest






Faculty/Professorship: Information Visualisation 
Author(s): Beck, Fabian  ; Krause, Cedric  
Title of the compilation: EuroVis 2022 - Posters
Corporate Body: The Eurographics Association
Publisher Information: Bamberg : Otto-Friedrich-Universität
Year of publication: 2022
Pages: 1-3
ISBN: 978-3-03868-185-4
Source/Other editions: EuroVis 2022 - Posters. Rome : The Eurographics Association, 2022. Rome : The Eurographics Association, 2022. - ISBN: 978-3-03868-185-4.
is version of: 10.2312/evp.20221110
Language(s): English
Licence: German Act on Copyright 
DOI: 10.2312/evp.20221110
URL: https://conferences.eg.org/eurovis2022/
URN: urn:nbn:de:bvb:473-irb-542577
Abstract: 
Tracing citation links helps retrieve related publications. While most tools only allow the user to follow the citations of a single publication, some approaches support jointly analyzing the citations of a set of publications. Along similar lines, PURE suggest provides a detailed visual explanation of the ranking of suggested publications. The ranking is based on a score that combines citation numbers with keyword matching and is shown as a glyph for each publication. A citation network component references this glyph and visually embeds it into a timeline and cluster visualization.
GND Keywords: Literaturrecherche; Quellenangabe; Visualisierung
Keywords: literature search, citation network visualization
DDC Classification: 004 Computer science  
RVK Classification: SK 890   
Peer Reviewed: Ja
International Distribution: Ja
Type: Conferenceobject
URI: https://fis.uni-bamberg.de/handle/uniba/54257
Release Date: 20. July 2022

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