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A Multi-layer Event Visualization for Exploring User Search Patterns in Literature Discovery with PUREsuggest
Rabsahl, Solveig; Beck, Fabian (2024): A Multi-layer Event Visualization for Exploring User Search Patterns in Literature Discovery with PUREsuggest, in: Alexander Maedche, Michael Beigl, Kathrin Gerling, u. a. (Hrsg.), MuC ’24: Proceedings of Mensch und Computer 2024, New York: ACM, S. 408–412, doi: 10.1145/3670653.3677502.
Faculty/Chair:
Author:
Title of the compilation:
MuC '24: Proceedings of Mensch und Computer 2024
Editors:
Conference:
Mensch und Computer 2024 ; Karlsruhe, Germany
Publisher Information:
Year of publication:
2024
Pages:
ISBN:
979-8-4007-0998-2
Language:
English
Abstract:
Understanding user behavior is at the heart of user interface design, but can only be quantified to some extent. Qualitatively analyzing individual usage sessions is especially important in open-ended tasks like literature search. In this paper, we present a visual representation of logging data that provides the basis for an in-depth analysis and annotation of search and exploration sessions. The visualization was developed to evaluate the citation-based literature discovery tool PUREsuggest and is thus aimed at visualizing logging data of a literature search system. Events are represented on a timeline in different layers as bars and icon-based glyphs, and contextualized by the additional visualization of item states and active user-set search modifiers such as filters or keywords throughout the session. We demonstrate the applicability of the visualization by evaluating excerpts of two user sessions as an example.
GND Keywords: ; ;
Benutzerverhalten
Visualisierung
Literaturrecherche
Keywords: ; ;
User Behavior
Event Visualization
Literature Search
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Type:
Conferenceobject
Activation date:
November 18, 2024
Versioning
Question on publication
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https://fis.uni-bamberg.de/handle/uniba/104685