Re: [igraph] Cliques Doubt (Subgraph Weighted Edges)

[Gábor Csárdi]

Surendar,

frankly, I don't know what you want to do. The clique finding
algorithms ignore the weights, so not much use of experimenting with
them.

Maybe you want a weighted community finding algorithm?

Best,
G.

2009/4/2 Surendar Swaminathan <address@hidden>:
> Hello Graph Experts,
>
>  I am trying to do subgraph with in a graph those that are highly connected.
> Clique is not producing what I am looking for.
>
> I am worried because I have 500 nodes and reading the output to find the
> largest highly connected nodes from clique and move in to less highly
> connected nodes(Triads). I am not interested in Diads.If a node is selected
> for one of the subgraph it should not be selected with the next subgraph.
>
> I did do some experiment creating small graph and changing edge weights
> between nodes.
>
>  I created six nodes A,B,C,D,E,F
>
> Weights are the number of articles the two nodes have worked together.
>
>  example: Node” A” and  Node” B” have worked only in one article. Node "E"
> and "F" have worked 5 articles together. Likewise “A”,”B”,”D” have worked
> together in 1 article. B,C,D have worked 1 article together. A & C have
> never worked together.
>
> Created csv file with weight as one attribute. Converted it to Graph object
> and ran Cliques(graph).
>
> Example 2 :
>
> Node1
>
> Node2
>
> weight
>
> a
>
> b
>
> 5
>
> b
>
> d
>
> 5
>
> c
>
> d
>
> 1
>
> a
>
> d
>
> 5
>
> b
>
> c
>
> 1
>
> a
>
> c
>
> 5
>
> d
>
> e
>
> 5
>
> e
>
> h
>
> 5
>
>
>
> [[1]]
>
> [1] 0
>
>
>
> [[2]]
>
> [1] 1
>
>
>
> [[3]]
>
> [1] 2
>
>
>
> [[4]]
>
> [1] 3
>
>
>
> [[5]]
>
> [1] 4
>
> [[6]]
>
> [1] 5
>
>
>
> [[7]]
>
> [1] 0 1
>
>
>
> [[8]]
>
> [1] 0 2
>
>
>
> [[9]]
>
> [1] 0 3
>
>
>
> [[10]]
>
> [1] 1 2
>
>
>
> [[11]]
>
> [1] 1 3
>
>
>
> [[12]]
>
> [1] 2 3
>
>
>
> [[13]]
>
> [1] 3 4
>
>
>
> [[14]]
>
> [1] 4 5
>
>
>
> [[15]]
>
> [1] 0 1 2
>
>
>
> [[16]]
>
> [1] 0 1 3
>
>
>
> [[17]]
>
> [1] 0 2 3
>
>
>
> [[18]]
>
> [1] 1 2 3
>
>
>
> [[19]]
>
> [1] 0 1 2 3
>
>  The final iteration is not something I am looking for. Node C should not be
> included in my clique final answer because Node C and Node D have worked
> only one article even though Node A and Node C have worked 5 times
> together.There is no closed loop Node C can fit into. Here is my requirement
>  A,B,D have published 5 articles together and they seem to be working
> together more than any other triads and  final clique says 0,1,2,3 .So the
> final answer is ABD and no other subgraph is correct given the weights and
> the nodes that has been used for one of the subgraph should not be used for
> the other subgraph.
>
> Only the iteration #16 gives me proper result.
>
> * [[16]]*
>
> *[1] 0 1 3*
>
> This should be final answer. Is there anyway I can do.
>
>  I hope graph experts can understand. Clique is not the desired solution for
> me and I have no other idea  work around for this. I am sorry about the long
> email.
>
>
>
>
> On Thu, Apr 2, 2009 at 9:46 AM, Surendar Swaminathan <
> address@hidden> wrote:
>
>> O.k so the better way to proceed is to use weighted graph rather than using
>> multiple links.
>>
>>
>> On Thu, Apr 2, 2009 at 12:24 AM, Gábor Csárdi <address@hidden> wrote:
>>
>>> 2009/4/2 Surendar Swaminathan <address@hidden>:
>>> > Hello Gabor,
>>> >
>>> >   Thanks for the reply.I understand what you are saying betweenness and
>>> > Eigen Values changes between multiple link and single link I have tried
>>> and
>>> > they are different.The program works perfectly fine if I input the
>>> multiple
>>> > nodes the way I feed.
>>>
>>> It is one thing that the functions terminate without an error message
>>> and it is another thing whether the results actually make sense.
>>>
>>> Now that I think about it, eigenvector centrality should be good, as
>>> well. It does the same as it would on the corresponding weighted
>>> graph.
>>>
>>> Still not sure about betweenness, though.
>>>
>>> Best,
>>> Gabor
>>>
>>> > With respect to the cliques I will work on them.I tried before I will
>>> cross
>>> > check once more.
>>> >
>>> > Nathan
>>> >
>>> [...]
>>>
>>> --
>>>  Gabor Csardi <address@hidden>     UNIL DGM
>>>
>>>
>>> _______________________________________________
>>> igraph-help mailing list
>>> address@hidden
>>> http://lists.nongnu.org/mailman/listinfo/igraph-help
>>>
>>
>>
>
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>



-- 
Gabor Csardi <address@hidden>     UNIL DGM