How to get node names from the dataset not like 1,2,3

I have a df containing 3 columns ( from, to, new_ssp ). The from and to columns are the node and the new_ssp is the score/weight column. The range of the new_ssp is from 0 to 1.

The node name is fully different in my dataset like (IDxx, FID_XX), etc, When I am running the code, I am getting output which containing the node names like (1,2,3,4) below one!

My dataset looks like

                              from  to    new_ssp
1                           ID00104 ID09099 0.92582160
2 ID00925 _ SID13505 _ Taraxerol DB00104 0.07857143

My code

graph_datset <- df
graph_build <- graph_from_data_frame(graph_datset, directed = FALSE)
E(graph_build)$weight <- graph_datset$new_ssp
plot(graph_build, vertex.label = V(graph_build)$name)

# Calculating New link prediction using 'linkprediction'
  proxfun(graph_build, method="cos", value="matrix")

Generated output look likes

  1        2        3
1 0 0.000000 0.000000
2 0 0.000000 1.442695
3 0 1.442695 0.000000

Now the problem is

  1. Is it possible to get the output node names from the dataset instead of 1/2/3? Because, this is very difficult for me to match my input node name and output node name!
  2. I have found, when I am using only 2 columns from and to I am getting the same output at the time of 3 columns from, to, and score/weight. Is it possible to use weight and take this weight to calculate the link prediction? Because, the weight must have some significance to predict the new link.


If this matrix contains all vertices, I suppose the row and column names would be V(graph_build)$name right?


Thank you. Yes, but the problem is, when I am running this line of the code

I am getting 1/2/3 not from my dataset node name!

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