International Conference on Human Interface and the Management of Information

HCI 2015: Human Interface and the Management of Information. Information and Knowledge in Context pp 89-100 | Cite as

What Should I Read Next? A Personalized Visual Publication Recommender System

  • Simon Bruns
  • André Calero Valdez
  • Christoph Greven
  • Martina Ziefle
  • Ulrik Schroeder
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9173)

Abstract

Discovering relevant publications for researchers is a non-trivial task. Recommender systems can reduce the effort required to find relevant publications. We suggest using a visualization- and user-centered interaction model to achieve both a more trusted recommender system and a system to understand a whole research field. In a graph-based visualization papers are aligned with their keywords according to the relevance of the keywords. Relevance is determined using text-mining approaches. By letting the user control relevance thresholds for individual keywords we have designed a recommender system that scores high in accuracy (\(\bar{x}=5.03/6\)), trust (\(\bar{x}=4.31/6\)) and usability (SUS \(\bar{x}=4.89/6\)) in a user study, while at the same time providing additional information about the field as a whole. As a result, the inherent trust issues conventional recommendation systems have seem to be less significant when using our solution.

Keywords

Recommender systems Visualization User-study Trust Usability 

Notes

Acknowledgments

We would like to thank the anonymous reviewers for their constructive comments on an earlier version of this manuscript. The authors thank the German Research Council DFG for the friendly support of the research in the excellence cluster “Integrative Production Technology in High Wage Countries”.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Simon Bruns
    • 1
  • André Calero Valdez
    • 1
  • Christoph Greven
    • 2
  • Martina Ziefle
    • 1
  • Ulrik Schroeder
    • 2
  1. 1.Human-Computer Interaction CenterRWTH Aachen UniversityAachenGermany
  2. 2.Learning Technologies Research GroupRWTH Aachen UniversityAachenGermany

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