ATTention: Understanding Authors and Topics in Context of Temporal Evolution

  • Nasir Naveed
  • Sergej Sizov
  • Steffen Staab
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6611)

Abstract

Understanding thematic trends and user roles is an important challenge in the field of information retrieval. In this contribution, we present a novel model for analyzing evolution of user’s interests with respect to produced content over time. Our approach ATTention (a name derived from analysis of Authors and Topics in the Temporal context) addresses this problem by means of Bayesian modeling of relations between authors, latent topics and temporal information. We also present results of preliminary evaluations with scientific publication datasets and discuss opportunities of model use in novel mining and recommendation scenarios.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Nasir Naveed
    • 1
  • Sergej Sizov
    • 1
  • Steffen Staab
    • 1
  1. 1.Institute for Web Science and TechnologiesUniversity of Koblenz-LandauGermany

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