On Distance Functions Between Closure Systems and Their Application in Industrial Maps

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F25%3A73634459" target="_blank" >RIV/61989592:15310/25:73634459 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-032-03364-2_19" target="_blank" >http://dx.doi.org/10.1007/978-3-032-03364-2_19</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-032-03364-2_19" target="_blank" >10.1007/978-3-032-03364-2_19</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On Distance Functions Between Closure Systems and Their Application in Industrial Maps

Popis výsledku v původním jazyce

By measuring the distance between closure systems, we can assess how closely two datasets or knowledge structures are related. In this paper, we propose distance functions for comparing closure systems, which can also be applied to concept lattices built on the same set of objects with varying attribute sets. Our proposed methods were implemented in the Go programming language. In our practical application, we examined industry maps from 63 school world atlases, originating from 23 countries and 40 publishers, from 1938 to 2018. We compare the distances between concept lattices constructed from three sets of map attributes: industrial sectors (13 attributes), power plants, pipelines, and material transport (12 attributes), and minerals (45 attributes). Our results demonstrate that the proposed distance functions could effectively capture structural differences between thematic layers of industrial maps, reflecting their varying conceptual complexity.

Název v anglickém jazyce

On Distance Functions Between Closure Systems and Their Application in Industrial Maps

Popis výsledku anglicky

By measuring the distance between closure systems, we can assess how closely two datasets or knowledge structures are related. In this paper, we propose distance functions for comparing closure systems, which can also be applied to concept lattices built on the same set of objects with varying attribute sets. Our proposed methods were implemented in the Go programming language. In our practical application, we examined industry maps from 63 school world atlases, originating from 23 countries and 40 publishers, from 1938 to 2018. We compare the distances between concept lattices constructed from three sets of map attributes: industrial sectors (13 attributes), power plants, pipelines, and material transport (12 attributes), and minerals (45 attributes). Our results demonstrate that the proposed distance functions could effectively capture structural differences between thematic layers of industrial maps, reflecting their varying conceptual complexity.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název statě ve sborníku

Conceptual Knowledge Structures

ISBN

978-3-032-03363-5

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

12

Strana od-do

295-306

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Cluj-Napoca

Datum konání akce

8. 9. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—