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On Terrain Coverage Optimization by Using a Network Approach for Universal Graph-Based Data Mining and Knowledge Discovery

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 8609)

Abstract

This conceptual paper discusses a graph-based approach for on-line terrain coverage, which has many important research aspects and a wide range of application possibilities, e.g in multi-agents. Such approaches can be used in different application domains, e.g. in medical image analysis. In this paper we discuss how the graphs are being generated and analyzed. In particular, the analysis is important for improving the estimation of the parameter set for the used heuristic in the field of route planning. Moreover, we describe some methods from quantitative graph theory and outline a few potential research routes.

Keywords

  • Knowledge Discovery
  • Route Planning
  • Social Ontology
  • Network Biology
  • Graph Edit Distance

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Preuß, M., Dehmer, M., Pickl, S., Holzinger, A. (2014). On Terrain Coverage Optimization by Using a Network Approach for Universal Graph-Based Data Mining and Knowledge Discovery. In: Ślȩzak, D., Tan, AH., Peters, J.F., Schwabe, L. (eds) Brain Informatics and Health. BIH 2014. Lecture Notes in Computer Science(), vol 8609. Springer, Cham. https://doi.org/10.1007/978-3-319-09891-3_51

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  • DOI: https://doi.org/10.1007/978-3-319-09891-3_51

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09890-6

  • Online ISBN: 978-3-319-09891-3

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