PUREsuggest : Citation-based Literature Search and Visual Exploration with Keyword-controlled Rankings

Citations allow quickly identifying related research. If multiple publications are selected as seeds, specifc suggestions for related literature can be made based on the number of incoming and outgoing citation links to this selection. Interactively adding recommended publications to the selection r...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - PP(2024) vom: 10. Sept.
1. Verfasser: Beck, Fabian (VerfasserIn)
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article
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520 |a Citations allow quickly identifying related research. If multiple publications are selected as seeds, specifc suggestions for related literature can be made based on the number of incoming and outgoing citation links to this selection. Interactively adding recommended publications to the selection refnes the next suggestion and incrementally builds a relevant collection of publications. Following this approach, the paper presents a search and foraging approach, PUREsuggest, which combines citation-based suggestions with augmented visualizations of the citation network. The focus and novelty of the approach is, frst, the transparency of how the rankings are explained visually and, second, that the process can be steered through user-defned keywords, which refect topics of interests. The system can be used to build new literature collections, to update and assess existing ones, as well as to use the collected literature for identifying relevant experts in the feld. We evaluated the recommendation approach through simulated sessions and performed a user study investigating search strategies and usage patterns supported by the interface 
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