Title :
Edge rough graph and its application
Author :
Meilian Liang ; Binmei Liang ; Linna Wei ; Xiaodong Xu
Author_Institution :
Sch. of Math. & Inf. Sci., Guangxi Univ., Nanning, China
Abstract :
Mining data that is represented as a graph by rough set theory is studied in this paper. Edge rough graph is first introduced, which can be easily combined with many powerful methods developed in graph theory, to deal with uncertainty, inconsistency and incompleteness in data represented as graphs. Then based on the notion of group, a specific relation over the edge set of a graph is defined, by which any graph can be approximated by a pair of Cayley graphs. An application of edge rough graph in computing bounds on clique numbers of graphs is given.
Keywords :
data mining; graph theory; rough set theory; Cayley graphs; clique numbers; data mining; edge rough graph; graph theory; rough set theory; Approximation methods; Data mining; Educational institutions; Graph theory; Information systems; Rough sets; Cayley graph; Data mining; Graph mining; Rough graph; Rough set;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6019588
