We introduce a model of uncertainty where documents are not uniquely identified in a reference network, and some links may be incorrect. It generalizes the probabilistic approach ...
Abstract. We introduce classes of graphs with bounded expansion as a generalization of both proper minor closed classes and degree bounded classes. Such classes are based on a new ...
The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generaliz...
Abstract. In a recommender system where users rate items we predict the rating of items users have not rated. We define a rating graph containing users and items as vertices and r...
— Finding decompositions of a graph into a family of clusters is crucial to understanding its underlying structure. While most existing approaches focus on partitioning the nodes...