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Chain of Influencers: Multipartite Intra-community Ranking

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238634" target="_blank" >RIV/61989100:27240/17:10238634 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-319-62389-4_50#enumeration" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-62389-4_50#enumeration</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-62389-4_50" target="_blank" >10.1007/978-3-319-62389-4_50</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Chain of Influencers: Multipartite Intra-community Ranking

  • Original language description

    Ranking of vertices is an important part of social network analysis. However, thanks to the enormous growth of real-world networks, the global ranking of vertices on a large scale does not provide easily comparable results. On the other hand, the ranking can provide clear results on a local scale and also in heterogeneous networks where we need to work with vertices of different types. In this paper, we present a method of ranking objects in a community which is closely related to the analysis of heterogeneous information networks. Our method assumes that the community is a set of several groups of objects of different types where each group, so-called object pool, contains objects of the same type. These community object pools can be connected and ordered to the chain of influencers, and ranking can be applied to this structure. Based on the chain of influencers, the heterogeneous network can be converted to a multipartite graph. In our approach, we show how to rank vertices of the community using the mutual influence of community object pools. In our experiments, we worked with a computer science research community. Objects of this domain contain authors, papers (articles), topics (keywords), and years of publications. © 2017, Springer International Publishing AG.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 10392

  • ISBN

    978-3-319-62388-7

  • ISSN

    0302-9743

  • e-ISSN

    1611-3349

  • Number of pages

    12

  • Pages from-to

    603-614

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Hongkong

  • Event date

    Aug 3, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article