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Multi-Entity Bayesian Networks for Knowledge-Driven Analysis of ICH Content

  • Giannis Chantas
  • Alexandros Kitsikidis
  • Spiros Nikolopoulos
  • Kosmas Dimitropoulos
  • Stella Douka
  • Ioannis Kompatsiaris
  • Nikos Grammalidis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8926)

Abstract

In this paper we introduce Multi-Entity Bayesian Networks (MEBNs) as the means to combine first-order logic with probabilistic inference and facilitate the semantic analysis of Intangible Cultural Heritage (ICH) content. First, we mention the need to capture and maintain ICH manifestations for the safeguarding of cultural treasures. Second, we present the MEBN models and stress their key features that can be used as a powerful tool for the aforementioned cause. Third, we present the methodology followed to build a MEBN model for the analysis of a traditional dance. Finally, we compare the efficiency of our MEBN model with that of a simple Bayesian network and demonstrate its superiority in cases that demand for situation-specific treatment.

Keywords

Semantic analysis Intangible cultural heritage Multi-entity bayesian networks 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Giannis Chantas
    • 1
  • Alexandros Kitsikidis
    • 1
  • Spiros Nikolopoulos
    • 1
  • Kosmas Dimitropoulos
    • 1
  • Stella Douka
    • 2
  • Ioannis Kompatsiaris
    • 1
  • Nikos Grammalidis
    • 1
  1. 1.Centre for Research and Technology HellasInformation Technologies InstituteThessalonikiGreece
  2. 2.Department of Physical Education and Sport ScienceAristotle University of ThessalonikiThessalonikiGreece

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