Improving Semantic Relatedness in Paths for Storytelling with Linked Data on the Web

  • Laurens De Vocht
  • Christian Beecks
  • Ruben Verborgh
  • Thomas Seidl
  • Erik Mannens
  • Rik Van de Walle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9341)

Abstract

Algorithmic storytelling over Linked Data on the Web is a challenging task in which many graph-based pathfinding approaches experience issues with consistency regarding the resulting path that leads to a story. In order to mitigate arbitrariness and increase consistency, we propose to improve the semantic relatedness of concepts mentioned in a story by increasing the relevance of links between nodes through additional domain delineation and refinement steps. On top of this, we propose the implementation of an optimized algorithm controlling the pathfinding process to obtain more homogeneous search domain and retrieve more links between adjacent hops in each path. Preliminary results indicate the potential of the proposal.

Notes

Acknowledgment

This work is partially Funded by the Excellence Initiative of the German federal and state governments; Flanders (IWT, FWO); and the European Union.

References

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Laurens De Vocht
    • 1
  • Christian Beecks
    • 2
  • Ruben Verborgh
    • 1
  • Thomas Seidl
    • 2
  • Erik Mannens
    • 1
  • Rik Van de Walle
    • 1
  1. 1.Multimedia LabGhent University - iMindsGhentBelgium
  2. 2.Department of Computer Science 9, Data Management and Data Exploration GroupRWTH Aachen UniversityAachenGermany

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