Abstract. This paper is on the automation of knowledge-intensive tasks in engineering domains; here, the term “task” relates to analysis and synthesis tasks, such as diagnosis ...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
Ontology learning is an important task in Artificial Intelligence, Semantic Web and Text Mining. This paper presents a novel framework for, and solutions to, three practical probl...
Abstract— Over the last years, interest in hybrid metaheuristics has risen considerably in the field of optimization. Combinations of methods such as evolutionary algorithms and...