Visualizing item similarities I have an implicit dataset. It contains which user click which item. I'm doing collaborative filtering and finally i get the item similarites. So now i have data like;

Item - SimilarItem - SimilarityValue
A    - C           - 0.12
A    - R           - 0.42
A    - Y           - 0.34
A    - J           - 0.62
B    - A           - 0.16
B    - Y           - 0.83
C    - J           - 0.23


or 

Item  --  Similarities
A     --  C,R,Y,J
B     --  A,Y
C     --  J,A,D


As i know all the relations between 40K item, can i turn this into a nice visualization showing some of them get together at somewhere and someothers are elsewhere. I can do this either with python or some javascript library.

What should be the way of doing this? Can you show me some examples?
You could treat your results as an undirected graph with weighted edges. Your nodes are A, B, C, etc. and your vertices are the connections between items, weighted by similarity value.

Here is a Python function that could be a great starting point. It draws thicker connections for vertices with a larger weight. I copied it and replaced the example data with your data points above:

[...]
node_list = ['A', 'B', 'C', 'D', 'J', 'R', 'Y']
[...]
G.add_edge(node_list[0],node_list[2],weight=0.12) # A - C
G.add_edge(node_list[0],node_list[5],weight=0.42) # A - R
G.add_edge(node_list[0],node_list[6],weight=0.34) # A - Y
G.add_edge(node_list[0],node_list[4],weight=0.62) # A - J
G.add_edge(node_list[0],node_list[1],weight=0.16) # A - B
G.add_edge(node_list[0],node_list[6],weight=0.83) # B - Y
G.add_edge(node_list[2],node_list[4],weight=0.21) # C - J


The result is this:



Of course, if you have 40,000 items, that would probably require additional work to make the plot comprehensible. You could begin by ignoring all connections between nodes with a similarity value of, say, 0.01 or less.