Ontology Learning from Text: Methods, Evaluation and Applications (Frontiers in Artificial Intelligence and Applications)

Buitelaar; P.; Cimiano; Magnini; B.

ISBN 10: 1586035231 / ISBN 13: 9781586035235

Verlag: IOS Press, 2005

Beschreibung

In. Bestandsnummer des Verkäufers ria9781586035235_new

Bibliografische Details

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

Verlag: IOS Press

Erscheinungsdatum: 2005

Einband: Hardcover

Zustand: New

Über diesen Titel

Inhaltsangabe:

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.

Aus dem Klappentext:

"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.