Abstract. The foundation of a process model lies in its control flow specifications. Using a generic process modeling language for workflows, we show how a control flow specificati...
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Dense sub-graphs of sparse graphs (communities), which appear in most real-world complex networks, play an important role in many contexts. Most existing community detection algori...
The way the graph structure of the constraints influences the complexity of constraint satisfaction problems (CSP) is well understood for bounded-arity constraints. The situation...
This paper shows how language technologies such as the automatic generation of parsers for analyzing user actions and visual parsing can be applied to build a flexible tool specia...