algorithm - Graph Theory: Calculating Clustering Coefficient -



algorithm - Graph Theory: Calculating Clustering Coefficient -

i'm doing research , i've come point have calculate clustering coefficient of graph.

according this paper straight related research:

the clustering coefficient c(p) defined follows. suppose vertex v has kv neighbours; @ (kv * (kv-1)) / 2 edges can exist between them (this occurs when every neighbour of v connected every other neighbour of v). allow cv denote fraction of these allowable edges exist. define c average of cv on v

but this wikipedia article on subject says differently:

c = (number of closed triplets) / (number of connected triples)

it seems me latter more computationally expensive.

so question is: equivalent?

it should noted paper cited wikipedia article.

thanks time.

i think they're equivalent. wiki page link gives proof triples formulation equivalent fraction of possible edges formulation when calculating local clustering coefficient, i.e. calculated @ vertex. there seems need show that

sum_v lambda(v)/tau(v) = 3 x # triangles / # connected triples

where lambda(v) number of triangles containing v, , tau(v) number of connected triples v middle vertex, i.e. adjacent each of other 2 edges.

now each triangle gets counted 3 times in numerator of lhs. however, each connected triple counted 1 time middle vertex on lhs, denominators same.

algorithm cluster-analysis graph-theory

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