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A hierarchical overlapping community detection method based on closed trail distance and maximal cliques

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10254116" target="_blank" >RIV/61989100:27240/24:10254116 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0020025524001841" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0020025524001841</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.ins.2024.120271" target="_blank" >10.1016/j.ins.2024.120271</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A hierarchical overlapping community detection method based on closed trail distance and maximal cliques

  • Original language description

    An important feature of real networks is their hierarchy and the existence of overlapping communities. Hierarchical agglomerative clustering is one way to determine the hierarchy of a network. To ensure the existence of overlapping communities, it is appropriate to choose the base elements for clustering - edges, cliques, etc. These base elements can then have common vertices and naturally provide the possibility of overlap. The proposed community detection method uses hierarchical agglomerative clustering on the 2-edge-connected component of the graph. Communities are constructed from maximal cliques as base elements. Novel dissimilarities for hierarchical agglomerative clustering were introduced for the merging of cliques. The dissimilarities use the size of the overlapped cliques and closed trail distance to express dissimilarity between communities in networks. The single linkage approach contains and extends the results of k-CPM. The proposed algorithm utilizing deterministic dissimilarity achieves comparable or superior outcomes compared to standard algorithms used for hierarchical or overlapping community detection.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Information sciences

  • ISSN

    0020-0255

  • e-ISSN

    1872-6291

  • Volume of the periodical

    662

  • Issue of the periodical within the volume

    Březen

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    15

  • Pages from-to

    120271

  • UT code for WoS article

    001182241200001

  • EID of the result in the Scopus database