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Visual Exploration of Relationships between Document Clusters
Linnaeus University, Faculty of Technology, Department of Computer Science.ORCID iD: 0000-0001-6745-4398
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-0519-2537
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0003-3654-0255
2014 (English)In: IVAPP 2014: Proceedings od the 5th International Conference on Information Visualization Theory and Applications / [ed] Robert S. Laramee, Andreas Kerren, José Braz, SciTePress, 2014, p. 195-203Conference paper, Published paper (Refereed)
Abstract [en]

The visualization of networks with additional attributes attached to the network elements is one of the ongoing challenges in the information visualization domain. Such so-called multivariate networks regularly appear in various application fields, for instance, in data sets which describe friendship networks or co-authorship networks. Here, we focus on networks that are based on text documents, i.e., the network nodes represent documents and the edges show relationships between them. Those relationships can be derived from common topics or common co-authors. Attached attributes may be specific keywords (topics), keyword frequencies, etc. The analysis of such multivariate networks is challenging, because a deeper understanding of the data provided depends on effective visualization and interaction techniques that are able to bring all types of information together. In addition, automatic analysis methods should be used to support the analysis process of potentially large amounts of data. In this paper, we present a visualization approach that tackles those analysis problems. Our implementation provides a combination of new techniques that shows intra-cluster and inter-cluster relations while giving insight into the content of the cluster attributes. Hence, it facilitates the interactive exploration of the networks under consideration by showing the relationships between node clusters in context of network topology and multivariate attributes.

Place, publisher, year, edition, pages
SciTePress, 2014. p. 195-203
Keywords [en]
network visualization, multivariate data, clustering, document visualization, text visualization, interaction, visual analytics
National Category
Computer Sciences Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-30369Scopus ID: 2-s2.0-84907386499ISBN: 978-989-758-005-5 (print)OAI: oai:DiVA.org:lnu-30369DiVA, id: diva2:663589
Conference
5th International Conference on Information Visualization Theory and Applications (IVAPP), Lisbon, Portugal, 5-8 January, 2014
Available from: 2013-11-12 Created: 2013-11-12 Last updated: 2018-01-11Bibliographically approved

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Jusufi, IlirKerren, AndreasLiu, JiayiZimmer, Björn

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Citation style
  • apa
  • harvard1
  • ieee
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  • Other locale
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Output format
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  • asciidoc
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