Ontology Learning from Text: Methods, Evaluation and Applications

Front Cover
Paul Buitelaar, Philipp Cimiano, Bernardo Magnini
IOS Press, 2005 - Computers - 171 pages
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.
 

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Contents

An Overview
3
Methods
13
Taxonomy Extraction for Ontology Learning
15
Unsupervised Text Mining for the Learning of DOGMAInspired Ontologies
29
A Study on Automated Relation Labelling in Ontology Learning
44
Learning Taxonomic Relations from Heterogeneous Sources of Evidence
59
Evaluation
75
An Evaluation Framework for Ontology Enrichment
77
Evaluation of OntoLearn a Methodology for Autometic Learning of Domain Ontologies
92
A TaskBased Framework for Ontology Learning Population and Evaluation
107
Applications
123
An Automatic Extraction Method and Its Evaluation
125
Exploiting Technical Terminology for Knowledge Management
140
A Necessary Symbiosis
155
Author Index
171
Copyright

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