Learning Expressive Ontologies (Studies on the Semantic Web, Volume 2)

This publication advances the state-of-the-art in ontology learning by presenting a set of novel approaches to the semi-automatic acquisition, refinement and evaluation of logically complex axiomatizations. It has been motivated by the fact that the realization of the semantic web envisioned by Tim Berners-Lee is still hampered by the lack of ontological resources, while at the same time more and more applications of semantic technologies emerge from fast-growing areas such as e-business or life sciences. Such knowledge-intensive applications, requiring large scale reasoning over complex domains of interest, even more than the semantic web, depend on the availability of expressive, high-quality axiomatizations. This knowledge acquisition bottleneck could be overcome by approaches to the automatic or semi-automatic construction of ontologies. Hence a huge number of ontology learning tools and frameworks have been developed in recent years, all of them aiming for the automatic or semi-automatic generation of ontologies from various kinds of data. However, both the quality and the expressivity of ontologies that can be acquired by the current state-of-the-art in ontology learning so far have failed to meet the expectations of people who argue in favor of powerful, knowledge-intensive applications based on logical inference. This work therefore takes a first, yet important, step towards the semi-automatic generation and maintenance of expressive ontologies. IOS Press is an international science, technical and medical publisher of high-quality books for academics, scientists, and professionals in all fields. Some of the areas we publish in: • Biomedicine •Oncology • Artificial intelligence • Databases and information systems • Maritime engineering • Nanotechnology • Geoengineering • All aspects of physics • E-governance • E-commerce • The knowledge economy • Urban studies • Arms control • Understanding and responding to terrorism • Medical informatics • Computer Sciences