Similarity metrics vs human judgment of similarity for binary data: Which is best to predict typicality?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F24%3A73627221" target="_blank" >RIV/61989592:15310/24:73627221 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1568494624000449" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1568494624000449</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.asoc.2024.111270" target="_blank" >10.1016/j.asoc.2024.111270</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Similarity metrics vs human judgment of similarity for binary data: Which is best to predict typicality?

Popis výsledku v původním jazyce

Similarity measures for binary data have been subject to a number of comparative studies. In contrast to these studies, we provide a comparison of similarity measures with human judgment of similarity. For this purpose, we utilize the phenomenon of typicality, whose definition is based on similarity. We observe how well the similarity of objects – either computed by a similarity measure or provided by human judgment – enables the prediction of typicality of these objects in various human categories. In doing so, we examine a large variety of existing similarity measures, and utilize recently available extensive data involving binary data as well as data on human judgment of similarity and typicality.

Název v anglickém jazyce

Similarity metrics vs human judgment of similarity for binary data: Which is best to predict typicality?

Popis výsledku anglicky

Similarity measures for binary data have been subject to a number of comparative studies. In contrast to these studies, we provide a comparison of similarity measures with human judgment of similarity. For this purpose, we utilize the phenomenon of typicality, whose definition is based on similarity. We observe how well the similarity of objects – either computed by a similarity measure or provided by human judgment – enables the prediction of typicality of these objects in various human categories. In doing so, we examine a large variety of existing similarity measures, and utilize recently available extensive data involving binary data as well as data on human judgment of similarity and typicality.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

APPLIED SOFT COMPUTING

ISSN

1568-4946

e-ISSN

1872-9681

Svazek periodika

153

Číslo periodika v rámci svazku

MAR

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

13

Strana od-do

"111270-1"-"111270-13"

Kód UT WoS článku

001174778800001

EID výsledku v databázi Scopus

2-s2.0-85183188913