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Ontology Learning from Text: An Overview

Paul Buitelaar; Philipp Cimiano; Bernardo Magnini
In: Paul Buitelaar; Philipp Cimiano; Bernardo Magnini (Hrsg.). Ontology Learning from Text: Methods, Evaluation and Applications/ Frontiers in Artificial Intelligence and Applications. Vol. 123, IOS Press, 7/2005.


This volume brings together a collection of extended versions of selected papers from two workshops on ontology learning, knowledge acquisition and related topics that were organized in the context of the European Conference on Artificial Intelligence (ECAI) 2004 and the International Conference on Knowledge Engineering and Management (EKAW) 2004.

The volume presents current research in ontology learning, addressing three perspectives: methodologies that have been proposed to automatically extract information from texts and to give a structured organization to such knowledge, including approaches based on machine learning techniques; evaluation methods for ontology learning, aiming at defining procedures and metrics for a quantitative evaluation of the ontology learning task; and finally application scenarios that make ontology learning a challenging area in the context of real applications such as bio-informatics.

According to the three perspectives mentioned above, the book is divided into three ections, each including a selection of papers addressing respectively the methods, the applications and the evaluation of ontology learning approaches. However, all selected papers pay considerably attention to the evaluation perspective, as this was a central topic of the ECAI 2004 workshop out of which most of the papers in this volume originate.