Hi,
You can look at the Facebook Link Prediction Challenge on Kaggle where you
have to suggest links in a social Network.
The link for the forum for the contest is:
http://www.kaggle.com/c/FacebookRecruiting/forums
It has a lot of interesting approaches. One of them can be found at the
link below:
http://blog.echen.me/2012/07/31/edgepredictioninasocialgraphmysolutiontofacebooksuserrecommendationcontestonkaggle/
I am currently looking at a paper : Supervised Random Walks for Predicting
Links in social networks.
http://cs.stanford.edu/people/jure/pubs/linkpredwsdm11.pdf
I don't know If I can implement it in giraph. I will read the paper
completely and try to. Will keep you posted.
Thanks,
Ameya
On Thu, Oct 31, 2013 at 5:55 AM, Claudio Martella <
claudio.martella@gmail.com> wrote:
> I would assume that it depends on your data. A graph is a very general
> structure, and it is difficult to attack this problem in general. The most
> obvious one is transitive closure (if A is connected to B and B to C then A
> could be conntected to C). The triangle counting example in our codebase
> (although the name is misleading) is based on these kinds of assumptions.
>
>
> On Thu, Oct 31, 2013 at 1:26 PM, Pascal Jäger <pascal@pascaljaeger.de>wrote:
>
>> Hi,
>>
>> Does anyone happen to know a paper about link prediction using a pregel
>> like framework like Giraph?
>> Or has someone an idea about how link prediction could be accomplished
>> with Giraph?
>>
>> Any input is highly appreciated :)
>>
>> Thanks
>>
>> Pascal
>>
>>
>
>
> 
> Claudio Martella
> claudio.martella@gmail.com
>
