We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
Scale is often an issue with understanding and making sense of large social networks. Here we investigate methods for pruning social networks by determining the most relevant rela...
In collaborative indexing systems users generate a big amount of metadata by labelling web-based content. These labels are known as tags and form a shared vocabulary. In order to u...
This paper reviews worldwide activities on regional information spaces. In the US and Canada, a large number of community networks appeared in the early 1990s. As a platform for co...
Although recent research has shown that the complexity of a network depends on its structural organization, which is linked to the functional constraints the network must satisfy, ...