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Fuzzy Clustering of Incomplete Data by Means of Similarity Measures

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F19%3AA2001Y37" target="_blank" >RIV/61988987:17610/19:A2001Y37 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/abstract/document/8879844" target="_blank" >https://ieeexplore.ieee.org/abstract/document/8879844</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/UKRCON.2019.8879844" target="_blank" >10.1109/UKRCON.2019.8879844</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Fuzzy Clustering of Incomplete Data by Means of Similarity Measures

  • Original language description

    The current standing in the scope of Data Mining considers clustering to be one of the most useful and widely used tools. Multiple real-world datasets usually contain drops/gaps in the data due to various reasons. The currently known approaches are highly efficient only in those cases when original datasets do not change their volumes during the analysis. However, current problems mostly deal with sequential online data processing. On the other hand, there is no prior knowledge on which feature vectors contain overlooks. In this manuscript, the challenge of possibilistic and probabilistic online clustering approaches for processing incomplete data is solved through similarity measures of a specific kind which are capable of either loosening outliers’ influence or repressing them.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10102 - Applied mathematics

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of 2019 IEEE 2nd Ukraine Conference on Electrical and Computer Engineering (UKRCON)

  • ISBN

    978-1-7281-3882-4

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    957-960

  • Publisher name

    Institute of Electrical and Electronics Engineers Inc.

  • Place of publication

    Lvov, Ukrajina

  • Event location

    Lvov, Ukrajina

  • Event date

    Jul 2, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article