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On Confidentially Connected-Free Graphs

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Advances in Intelligent Analysis of Medical Data and Decision Support Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 473))

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Abstract

Graph theory provides algorithms and tools to handle models for important applications in biology and medicine, such as drug design, diagnosis, or visualization. This paper deals with some theoretical results concerning the relationship between two classes of graphs which may be susceptible of applications in medicine and intelligent systems. The class of Confidentially Connected-free graphs is introduced and related to the class of Asteroidal Triple-free graphs, as well as to the graphs that have a star-cutset. We give a characterization of Confidentially Connected-free graphs using neighborhoods and weakly decomposition.

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Author information

Authors and Affiliations

  1. ”Vasile Alecsandri” University, Bacau, Romania

    Mihai Talmaciu & Elena Nechita

  2. ”Petru Maior” University, Targu Mures, Romania

    Barna Iantovics

Authors
  1. Mihai Talmaciu
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  2. Elena Nechita
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  3. Barna Iantovics
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Corresponding author

Correspondence to Mihai Talmaciu .

Editor information

Editors and Affiliations

  1. Technical University of Sofia, Boul. Kl. Ohridsky 8, Sofia, 1000, Bulgaria

    Roumen Kountchev

  2. Petru Maior University, Str. Nicolae Iorga 1, Targu Mures, 540 088, Romania

    Barna Iantovics

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Talmaciu, M., Nechita, E., Iantovics, B. (2013). On Confidentially Connected-Free Graphs. In: Kountchev, R., Iantovics, B. (eds) Advances in Intelligent Analysis of Medical Data and Decision Support Systems. Studies in Computational Intelligence, vol 473. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00029-9_16

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  • DOI: https://doi.org/10.1007/978-3-319-00029-9_16

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00028-2

  • Online ISBN: 978-3-319-00029-9

  • eBook Packages: EngineeringEngineering (R0)

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