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Cause I'm a Genial Imprecise Point: Outlier Detection for Uncertain Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F21%3A00534694" target="_blank" >RIV/67985807:_____/21:00534694 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-030-67899-9_13" target="_blank" >http://dx.doi.org/10.1007/978-3-030-67899-9_13</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-67899-9_13" target="_blank" >10.1007/978-3-030-67899-9_13</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Cause I'm a Genial Imprecise Point: Outlier Detection for Uncertain Data

  • Original language description

    In this paper, we introduce the outlier detection problem in a set of uncertain points. We study two variants of the problems based upon the definition of the outlier. For a given positive integer k(<n) and a set R of n regions as the imprecise points, the first type of the outlier detection problem that we study is to locate n−k points on distinct regions, such that the size of the smallest axis-aligned bounding box (AABB), the diameter or the smallest enclosing circle (SEC) of the resulting points gets minimized. The uncertainty regions we study are squares or disks, and the excluded k regions are considered as outliers. We also study the covering versions in which the objectives of the SEC and the AABB problems are to find the smallest circle or axis-aligned bounding box, respectively, that covers the area of at least n−k regions. In the second-type of outliers, the outliers are those k regions that mostly reduce the uncertainty-induced gap between the lower bound and the upper bound on the size of the output. We give polynomial time algorithms for several variants of the mentioned problems, ranging in running time from O(nlogn) to O(n5.5logn) .

  • 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

    <a href="/en/project/GJ19-06792Y" target="_blank" >GJ19-06792Y: Structural properties of visibility in terrains and farthest color Voronoi diagrams</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Algorithms and Discrete Applied Mathematics

  • ISBN

    978-3-030-67898-2

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    14

  • Pages from-to

    165-178

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Rupnagar

  • Event date

    Feb 11, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article