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# Resource allocation vertex similarity
#
# Similarity measure based on resource allocation process.
#
# This function counts the number of common neighbours weighted by the inverse
# of their degrees.
#
similarity_ra <- function(graph, v1, v2, ...){
n <- igraph::vcount(graph)
score <- matrix(integer(n^2), nrow = n)
neighbors <- igraph::neighborhood(graph, 1)
neighbors <- lapply(neighbors, function(x) x[-1])
degrees <- igraph::degree(graph)
## inverse map
#invmap <- match(seq_along(neighbors), vertices_index)
for (k in seq(n)){
tmp <- neighbors[[k]]
l <- degrees[[k]]
if (l > 1){
for (i in 1:(l-1)){
n1 <- tmp[i]
# mapi <- invmap[[tmp[i]]]
# if (!is.na(mapi)){
for (j in (i+1):l){
# mapj <- invmap[[tmp[j]]]
# if (!is.na(mapj)){
# sim1[mapi, mapj] <- sim1[mapi, mapj] + 1/l
# sim1[mapj, mapi] <- sim1[mapj, mapi] + 1/l
# }
n2 <- tmp[j]
score[n1, n2] <- score[n1, n2] + 1/l
score[n2, n1] <- score[n2, n1] + 1/l
}
# }
}
}
}
score[v1, v2]
}
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