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Effect of Heuristics on Serendipity in Path-Based Storytelling with Linked Data

  • Laurens De Vocht
  • Christian Beecks
  • Ruben Verborgh
  • Erik Mannens
  • Thomas Seidl
  • Rik Van de Walle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9734)

Abstract

Path-based storytelling with Linked Data on the Web provides users the ability to discover concepts in an entertaining and educational way. Given a query context, many state-of-the-art pathfinding approaches aim at telling a story that coincides with the user’s expectations by investigating paths over Linked Data on the Web. By taking into account serendipity in storytelling, we aim at improving and tailoring existing approaches towards better fitting user expectations so that users are able to discover interesting knowledge without feeling unsure or even lost in the story facts. To this end, we propose to optimize the link estimation between - and the selection of facts in a story by increasing the consistency and relevancy of links between facts through additional domain delineation and refinement steps. In order to address multiple aspects of serendipity, we propose and investigate combinations of weights and heuristics in paths forming the essential building blocks for each story. Our experimental findings with stories based on DBpedia indicate the improvements when applying the optimized algorithm.

Keywords

Storytelling Serendipity Pathfinding A* Linked data Heuristics 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Laurens De Vocht
    • 1
  • Christian Beecks
    • 2
  • Ruben Verborgh
    • 1
  • Erik Mannens
    • 1
  • Thomas Seidl
    • 2
  • Rik Van de Walle
    • 1
  1. 1.Department of Electronics and Information SystemsGhent University - iMindsGhentBelgium
  2. 2.Data Management and Data Exploration GroupRWTH Aachen UniversityAachenGermany

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