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/edge-prediction-in-a-social-graph-my-solution-to-facebooks-user-recommendation-contest-on-kaggle/
I am currently looking at a paper : Supervised Random Walks for Predicting Links in social networks. http://cs.stanford.edu/people/jure/pubs/linkpred-wsdm11.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.marte...@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 <pas...@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.marte...@gmail.com >
