03081nam a22004695i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001600153072001500169072002300184072001400207100008300221245013800304250001800442264006900460300006600529336002600595337002600621338003600647347002400683490006200707505029300769520098401062650003402046650003202080650002902112650002202141650003202163650006102195700007902256710003402335773002602369776003602395776003602431776003602467830006202503856004602565978-3-031-53096-8DE-He21320251030111448.0cr nn 008mamaa240227s2024    sz |    s    |||| 0|eng d  a97830315309687 a10.1007/978-3-031-53096-82doi 4aTA345-345.5 7aUN2bicssc 7aCOM0180002bisacsh 7aUN2thema1 aSzkatuła, Grażyna.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aBidirectional Comparison of Nominal Setsh[electronic resource] :bAsymmetry of Proximity /cby Grażyna Szkatuła, Maciej Krawczak.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXVII, 206 p. 51 illus., 18 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aStudies in Computational Intelligence,x1860-9503 ;v11400 aIntroduction and main assumptions -- Issues of asymmetry of data proximity -- Matching between ordinary sets -- Matching between sets with binary coding -- Matching between multisets -- Matching between fuzzy sets -- Matching between intuitionistic fuzzy sets -- Summary and perspectives.  aThe authors propose a novel measure of proximity between two sets of nominal elements. This measure describes the changes in the first set after adding the second set or changes in the second set after adding the first set. It is crucial to note that this measure is not symmetric, it means that the perturbation of the first set on the second set can be different than the perturbation of the opposition direction. The introduced set impact measure allows for the direct treatment of objects described by nominal-valued attributes. The ordinary sets, multisets, fuzzy sets, and the intuitionistic fuzzy sets are considered. The book is intended for data science professionals, philosophers as well as cognitive psychologists, who struggle with practical problems in which asymmetry of proximity of objects cannot be neglected. The use of the proposed measures of perturbation between compared objects can be very important in data mining or in exploration of Internet resources. 0aEngineeringxData processing. 0aComputational intelligence. 0aEngineering mathematics.14aData Engineering.24aComputational Intelligence.24aMathematical and Computational Engineering Applications.1 aKrawczak, Maciej.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303153095108iPrinted edition:z978303153097508iPrinted edition:z9783031530982 0aStudies in Computational Intelligence,x1860-9503 ;v114040uhttps://doi.org/10.1007/978-3-031-53096-8