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Authors: L. Shao 1 ; 2 ; S. Lengauer 1 ; H. Miri 3 ; M. Bedek 4 ; B. Kubicek 4 ; C. Kupfer 4 ; M. Zangl 4 ; B. Dienstbier 5 ; K. Jeitler 5 ; C. Krenn 5 ; T. Semlitsch 5 ; C. Zipp 5 ; D. Albert 4 ; A. Siebenhofer 5 ; 6 and T. Schreck 1

Affiliations: 1 Institute of Computer Graphics and Knowledge Visualization, Graz University of Technology, Austria ; 2 Fraunhofer Austria Center for Data Driven Design, Austria ; 3 Carnegie Mellon - KMITL (CMKL University), Thailand ; 4 Institute of Psychology, University of Graz, Austria ; 5 Institute of General Practice and Evidence-based Health Services Research, Medical University of Graz, Austria ; 6 Goethe University Frankfurt, Germany

Keyword(s): Information Visualization, Document Exploration, Topic Modeling, Interactive Retrieval, Close-Distant Reading.

Abstract: Documents typically show a linear structure in which the content can be accessed. However, linear reading is not always desired by users, nor is it the best presentation way, as information needs may be developing or changing over time, and users would thus want to extract the relevant information by navigation and search. Therefore, reading with adaptive focus and level of detail is needed. This is of utmost importance in the health information domain where patient conditions and resulting information needs may evolve in different directions over time. We report on the development of a visual document exploration system which supports navigating a document at different levels of aggregation, from topic overview (high-level) to keyword occurrences (mid-level) to full text (low-level). Our design smoothly integrates the different levels of detail from which the users can choose. The system is designed to track explored topics and use this information to suggest additional content. We evaluated the design and its corresponding web-based implementation through a formative user-study in the domain of diabetes health information. The evaluation confirmed that our design and implementation can raise interest and curiosity, and also allow users to efficiently navigate content of interest. (More)

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Paper citation in several formats:
Shao, L.; Lengauer, S.; Miri, H.; Bedek, M.; Kubicek, B.; Kupfer, C.; Zangl, M.; Dienstbier, B.; Jeitler, K.; Krenn, C.; Semlitsch, T.; Zipp, C.; Albert, D.; Siebenhofer, A. and Schreck, T. (2023). Visual Document Exploration with Adaptive Level of Detail: Design, Implementation and Evaluation in the Health Information Domain. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - IVAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 133-141. DOI: 10.5220/0011621800003417

@conference{ivapp23,
author={L. Shao. and S. Lengauer. and H. Miri. and M. Bedek. and B. Kubicek. and C. Kupfer. and M. Zangl. and B. Dienstbier. and K. Jeitler. and C. Krenn. and T. Semlitsch. and C. Zipp. and D. Albert. and A. Siebenhofer. and T. Schreck.},
title={Visual Document Exploration with Adaptive Level of Detail: Design, Implementation and Evaluation in the Health Information Domain},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - IVAPP},
year={2023},
pages={133-141},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011621800003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - IVAPP
TI - Visual Document Exploration with Adaptive Level of Detail: Design, Implementation and Evaluation in the Health Information Domain
SN - 978-989-758-634-7
IS - 2184-4321
AU - Shao, L.
AU - Lengauer, S.
AU - Miri, H.
AU - Bedek, M.
AU - Kubicek, B.
AU - Kupfer, C.
AU - Zangl, M.
AU - Dienstbier, B.
AU - Jeitler, K.
AU - Krenn, C.
AU - Semlitsch, T.
AU - Zipp, C.
AU - Albert, D.
AU - Siebenhofer, A.
AU - Schreck, T.
PY - 2023
SP - 133
EP - 141
DO - 10.5220/0011621800003417
PB - SciTePress