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Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00209805%3A_____%2F22%3A00079087" target="_blank" >RIV/00209805:_____/22:00079087 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216224:14330/22:00127569

  • Result on the web

    <a href="https://reader.elsevier.com/reader/sd/pii/S0893608022003896?token=87052F21165A84F9A10A2D99E68C26C9B30322FAA8182BD2B19D0A8AD0A1CAEB35F609AC4BEA2238E580F23CB27042A7&originRegion=eu-west-1&originCreation=20221110130755" target="_blank" >https://reader.elsevier.com/reader/sd/pii/S0893608022003896?token=87052F21165A84F9A10A2D99E68C26C9B30322FAA8182BD2B19D0A8AD0A1CAEB35F609AC4BEA2238E580F23CB27042A7&originRegion=eu-west-1&originCreation=20221110130755</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.neunet.2022.10.005" target="_blank" >10.1016/j.neunet.2022.10.005</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding

  • Original language description

    The scarcity of high-quality annotations in many application scenarios has recently led to an increasing interest in devising learning techniques that combine unlabeled data with labeled data in a network. In this work, we focus on the label propagation problem in multilayer networks. Our approach is inspired by the heat diffusion model, which shows usefulness in machine learning problems such as classification and dimensionality reduction. We propose a novel boundary-based heat diffusion algorithm that guarantees a closed-form solution with an efficient implementation. We experimentally validated our method on synthetic networks and five real-world multilayer network datasets representing scientific coauthorship, spreading drug adoption among physicians, two bibliographic networks, and a movie network. The results demonstrate the benefits of the proposed algorithm, where our boundary-based heat diffusion dominates the performance of the state-of-the-art methods.

  • 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

    10103 - Statistics and probability

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Neural networks: the official journal of the International Neural Network Society

  • ISSN

    0893-6080

  • e-ISSN

    1879-2782

  • Volume of the periodical

    156

  • Issue of the periodical within the volume

    December 2022

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    13

  • Pages from-to

    205-217

  • UT code for WoS article

    000886066900007

  • EID of the result in the Scopus database

    2-s2.0-85140088729