Ontology Learning from Text : Methods, Evaluation And Applications

Buitelaar, Paul (EDT); Cimiano, Philipp (EDT); Magnini, Bernardo (EDT)

ISBN 10: 1586035231 / ISBN 13: 9781586035235

Published by IOS Press, 2005

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Bibliographic Details

Title: Ontology Learning from Text : Methods, ...

Publisher: IOS Press

Publication Date: 2005

Binding: Hardcover

Condition: As New

About this title

Synopsis:

This volume brings together ontology learning, knowledge acquisition and other related topics. It presents current research in ontology learning, addressing three perspectives. The first perspective looks at 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. Then there are 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 sections, each including a selection of papers addressing respectively the methods, the applications and the evaluation of ontology learning approaches.

From the Inside Flap:

"This volume provides an excellent snapshot of the current state of the art in ontology learning and the related issue of ontology evaluation. It will be of interest not just to researchers involved in ontologies but also to the wider CL and NLP community who are interested to see where their component technologies are being used."- Christopher Brewster, Computational Linguistics

This volume brings together ontology learning, knowledge acquisition and other related topics. It presents current research in ontology learning, addressing three perspectives. The first perspective looks at 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. Then there are 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 sections, each including a selection of papers addressing respectively the methods, the applications and the evaluation of ontology learning approaches.