Konferenzbeitrag
Graph Complexity in visual recommender systems for scientific literature
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Dokumententyp
Text/Conference Paper
Datum
2016
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Quelle
Mensch und Computer 2016 – Workshopband
Human Factors in Information Visualization and Decision Support System
Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
Digital libraries are becoming larger, while suffering from inefficient interfaces and search patterns. Recommender Systems are a sensible and important service for users of digital libraries. The aim of recommender systems is to reduce cognitive effort, simplify search and to embed results in a larger context. In this article we compare to recommender systems – the Action Science Explorer and Papercube. Both systems are used to recommend scientific literature and use graph-based approaches. From user studies we derive the need for research to understand complexity of graphs.