Dear Alexander,

Thanks for your answer, regarding the treatment,
For example, if my data looks like


p1 p2 p3 p4 p5 p6
j1 1 0 1 0 1 0
j2 0 1 1 0 0 1
j3 0 0 0 1 1 1
j4 1 0 0 1 0 0

are you suggesting to treat it as


j1 j2 j3 j4 p1 p2 p3 p4 p5 p6
j1 0 0 0 0 1 0 1 0 1 0
j2 0 0 0 0 0 1 1 0 0 1
j3 0 0 0 0 0 0 0 1 1 1
j4 0 0 0 0 1 0 0 1 0 0
p1 1 0 0 1 0 0 0 0 0 0
p2 0 1 0 0 0 0 0 0 0 0
p3 1 1 0 0 0 0 0 0 0 0
p4 0 0 1 1 0 0 0 0 0 0
p5 1 0 1 0 0 0 0 0 0 0
p6 0 1 1 0 0 0 0 0 0 0

to be an adjacency matrix ?
Thanks,


On Tue, Mar 3, 2020 at 5:32 PM Alexandre Hannud Abdo <[email protected]>
wrote:

> Ni!
>
> Incidence matrices can be trated as a subset of an adjacency matrix (and
> in this sense hypergraphs as a special case of graphs), so in principle
> there is no problem to work around. You just need to properly interpret the
> model in terms of membership to hyperedges instead of connections to nodes.
>
> You should hardcode the bipartite structure when running the DL
> minimization in order to save processing time (see the pclabel param).
>
> If you're convinced that this doesn't suite your needs, you should
> explicitly formulate your conceptual issue so we can provide useful advice.
>
> Cheers!
>
> .~´
>
> On Tue, Mar 3, 2020 at 5:23 AM Alireza Kashani <
> [email protected]> wrote:
>
>> Thanks Alexander,
>>
>> May be my question was not clear enough - as you said, my data is already
>> an incident matrix.
>> I would like to use stochastic-block-models, and seems they only work
>> with adjacency matrices. Therefore, I wonder what are the possibilities to
>> work-around this problem.
>>
>> Br
>>
>>
>> On Mon, Mar 2, 2020 at 9:35 PM Alexandre Hannud Abdo <[email protected]>
>> wrote:
>>
>>> Ni! Hi Alireza,
>>>
>>> One way to work with hypergraphs is to use the incidence graph
>>> <https://en.wikipedia.org/wiki/Hypergraph> representation of the
>>> hypergraph.
>>>
>>> Abraços,
>>> ale
>>> .~´
>>>
>>> On Mon, Mar 2, 2020 at 5:28 PM Alireza Kashani <
>>> [email protected]> wrote:
>>>
>>>> Hi,
>>>>
>>>> I wonder how one can work with hyper-graphs using graph-tool. For
>>>> example in my work, I would like to feed a data where rows are journals and
>>>> columns are papers out-going citations. I understand such a binary matrix,
>>>> can not be used as an adjacency matrix but I am curious if it is possible
>>>> to work with this type of input. Otherwise, I appreciate to hear your
>>>> thoughts on converting this matrix into a adjacency matrix.
>>>>
>>>> Br
>>>> Alireza
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