TY - GEN

T1 - Structure analysis of fuzzy node fuzzy graph and its application to sociometry analysis

AU - Uesu, Hiroaki

PY - 2008

Y1 - 2008

N2 - We could generally analyze the inexact information efficiently and investigate the fuzzy relation by applying the fuzzy graph theory. We would extend the fuzzy graph theory, and propose a fuzzy node fuzzy graph. And we transform it to a fuzzy graph by using T-norm family. In this paper, we would discuss about four subjects, (1) fuzzy node fuzzy graph, (2) new T-norm "quasi logical product", (3) decision analysis of the optimal fuzzy graph in the fuzzy graph sequence {G λ }. By using the fuzzy node fuzzy graph theory and this new T-norm, we could clarify the relational structure of fuzzy information, and by using the decision of an optimal level on a partition tree, we could analyze the clustering relation among nodes. Moreover, we would illustrate its practical effectiveness with the case study concerning sociometry analysis.

AB - We could generally analyze the inexact information efficiently and investigate the fuzzy relation by applying the fuzzy graph theory. We would extend the fuzzy graph theory, and propose a fuzzy node fuzzy graph. And we transform it to a fuzzy graph by using T-norm family. In this paper, we would discuss about four subjects, (1) fuzzy node fuzzy graph, (2) new T-norm "quasi logical product", (3) decision analysis of the optimal fuzzy graph in the fuzzy graph sequence {G λ }. By using the fuzzy node fuzzy graph theory and this new T-norm, we could clarify the relational structure of fuzzy information, and by using the decision of an optimal level on a partition tree, we could analyze the clustering relation among nodes. Moreover, we would illustrate its practical effectiveness with the case study concerning sociometry analysis.

KW - Fuzzy node fuzzy graph

KW - Sociometry analysis

KW - T-norm

UR - http://www.scopus.com/inward/record.url?scp=57749197554&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=57749197554&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-85567-5-11

DO - 10.1007/978-3-540-85567-5-11

M3 - Conference contribution

AN - SCOPUS:57749197554

SN - 3540855661

SN - 9783540855668

VL - 5179 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 84

EP - 91

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

T2 - 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008

Y2 - 3 September 2008 through 5 September 2008

ER -