On succinct representation of directed graphs

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    13 Citations (Scopus)

    Abstract

    Directed graphs encode meaningful dependencies among objects ubiquitously. This paper introduces new and simple representations for labeled directed graphs with the properties of being succinct (space is information-theoretically optimal); in which we avoid exploiting a-priori knowledge on digraph regularity such as triangularity, separability, planarity, symmetry and sparsity. Our results have direct implications to model directed graphs by using single integer numbers effectively, which is significant to enable canonical (generation of graph instances is unique) and efficient (coding and decoding take polynomial time) encodings for learning and optimization algorithms. To the best of our knowledge, the proposed representations are the first known in the literature.

    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages199-205
    Number of pages7
    ISBN (Electronic)9781509030156
    DOIs
    Publication statusPublished - 2017 Mar 17
    Event2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017 - Jeju Island, Korea, Republic of
    Duration: 2017 Feb 132017 Feb 16

    Other

    Other2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
    CountryKorea, Republic of
    CityJeju Island
    Period17/2/1317/2/16

    ASJC Scopus subject areas

    • Information Systems
    • Artificial Intelligence
    • Computer Science Applications
    • Computer Vision and Pattern Recognition

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  • Cite this

    Parque Tenorio, V., & Miyashita, T. (2017). On succinct representation of directed graphs. In 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017 (pp. 199-205). [7881738] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIGCOMP.2017.7881738