Visual Analysis and Exploration of Entity Relations in Document Collections

Markus John, Florian Heimerl, Ba-Anh Vu, Thomas Ertl

Abstract

Interactive text visualization can help users explore and gain insights into complex and often large document sets. One popular visualization strategy to represent such collections is to depict each document as a glyph in 2D space. These spaces have proven effective, especially when combined with interactive exploration methods. However, current exploratory approaches are largely limited to single areas of a 2D spatialization, lacking support for important comparative exploration and analysis tasks. In this paper, we extend a flexible focus+context exploration technique to tackle this challenge. In particular, based on practical tasks from the digital humanities, we focus on exploring and investigating relationships between entities in large document collections. Our approach uses natural language processing to extract characters and places, including information about their relationships. We then use linked views to facilitate visual analysis of extracted information artifacts. Based on two usage scenarios, we demonstrate successful applications of the approach and discuss its benefits and limitations.

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Paper Citation


in Harvard Style

John M., Heimerl F., Vu B. and Ertl T. (2018). Visual Analysis and Exploration of Entity Relations in Document Collections.In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-289-9, pages 244-251. DOI: 10.5220/0006614902440251


in Bibtex Style

@conference{ivapp18,
author={Markus John and Florian Heimerl and Ba-Anh Vu and Thomas Ertl},
title={Visual Analysis and Exploration of Entity Relations in Document Collections},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2018},
pages={244-251},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006614902440251},
isbn={978-989-758-289-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - Visual Analysis and Exploration of Entity Relations in Document Collections
SN - 978-989-758-289-9
AU - John M.
AU - Heimerl F.
AU - Vu B.
AU - Ertl T.
PY - 2018
SP - 244
EP - 251
DO - 10.5220/0006614902440251