Symbolic data analysis aims at generalizing some standard statistical data mining methods, such as those developed for classification tasks, to the case of symbolic objects (SOs). ...
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
—We introduce a new BDD-like data structure called Hybrid-Restriction Diagrams (HRDs) for the representation and manipulation of linear hybrid automata (LHA) state-spaces and pre...
Abstract. This paper presents a unifying framework to model casebased reasoning recommender systems (CBR-RSs). CBR-RSs have complex architectures and specialize the CBR problem sol...
This paper describes the tool CASPA, a new performance evaluation tool which is based on a Markovian stochastic process algebra. CASPA uses multi-terminal binary decision diagrams ...