Fuzzy consensus measure on verbal opinions

Autor:	Hsin-Hui Lin, Te-Min Chang, Wen-Feng Hsiao
Rok vydání:	2008
Předmět:	business.industry General Engineering Interval Scale computer.software_genre Fuzzy logic Computer Science Applications Artificial Intelligence Entropy (information theory) Artificial intelligence Data mining business computer Membership function Natural language processing Mathematics
Zdroj:	Expert Systems with Applications. 35:836-842
ISSN:	0957-4174
DOI:	10.1016/j.eswa.2007.07.040
Popis:	In the group decision-making process, consensus is an important indication of group agreement or reliability. Traditional methods to measure consensus refer mostly to gauging variance among the participants' opinions by transforming them into numbers in the interval scale. In this study we propose a new value-based measure, in which verbal opinions are transformed into values by means of fuzzy membership functions. To understand how the proposed method performs, we conduct two experiments to compare its performance with the variance-based methods and entropy measure. The results show that our method is more appropriate to account for participants' consensus judgments based on verbal opinions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::335b710e7c9c3039a77998422865384e https://doi.org/10.1016/j.eswa.2007.07.040 Zobrazit plný text záznamu Full Text from ScienceDirect