Ontology Learning for the Semantic Web

by Maedche, Alexander

• ISBN13: 9780792376569
• ISBN10: 0792376560
• Format: Hardcover
• Copyright: 2002-02-01
• Publisher: Kluwer Academic Pub

Summary

Ontology Learning for the Semantic Web explores techniques for applying knowledge discovery techniques to different web data sources (such as HTML documents, dictionaries, etc.), in order to support the task of engineering and maintaining ontologies. The approach of ontology learning proposed in Ontology Learning for the Semantic Web includes a number of complementary disciplines that feed in different types of unstructured and semi-structured data. This data is necessary in order to support a semi-automatic ontology engineering process. Ontology Learning for the Semantic Web is designed for researchers and developers of semantic web applications. It also serves as an excellent supplemental reference to advanced level courses in ontologies and the semantic web.

Table of Contents

List of Figures	ix
List of Tables	xiii
Preface	xv
Acknowledgments	xviii
Foreword	xix
R. Studer
Part I Fundamentals
Introduction	3	(8)
Motivation & Problem Description	3	(1)
Research Questions	4	(2)
Reader's Guide	6	(5)
Ontology --- Definition & Overview	11	(18)
Ontologies for Communication -- A Layered Approach	15	(6)
Development & Application of Ontologies	21	(4)
Conclusion	25	(4)
Layered Ontology Engineering	29	(30)
Ontology Engineering Framework	30	(4)
Layered Representation	34	(15)
Conclusion	49	(10)
Further Topics in Ontology Engineering	50	(1)
Ontology Learning for Ontology Engineering	51	(8)
Part II Ontology Learning for the Semantic Web
Ontology Learning Framework	59	(22)
A Taxonomy of Relevant Data for Ontology Learning	60	(6)
An Architecture for Ontology Learning	66	(7)
Overview of the Architecture Components	66	(2)
Ontology Engineering Workbench ONTOEDIT	68	(2)
Data Import & Processing Component	70	(1)
Algorithm Library	71	(1)
Graphical User Interface & Management Component	72	(1)
Phases of Ontology Learning	73	(5)
Import & Reuse	74	(1)
Extract	75	(1)
Prune	76	(1)
Refine	77	(1)
Conclusion	78	(3)
Data Import & Processing	81	(36)
Importing & Processing Existing Ontologies	83	(12)
Ontology Wrapper & Import	84	(1)
FCA-MERGE --- Bottom-Up Ontology Merging	85	(10)
Collecting, Importing & Processing Documents	95	(17)
Ontology-focused Document Crawling	95	(2)
Shallow Text Processing Using SMES	97	(8)
Semi-Structured Document Wrapper	105	(2)
Transforming Data into Relational Structures	107	(5)
Conclusion	112	(5)
Language Processing for Ontology Learning	112	(1)
Ontology Learning from Web Documents	113	(1)
(Multi-) Relational Data	114	(3)
Ontology Learning Algorithms	117	(34)
Algorithms for Ontology Extraction	118	(22)
Lexical Entry Extraction	118	(4)
Taxonomy Extraction	122	(8)
Non-Taxonomic Relation Extraction	130	(10)
Algorithms for Ontology Maintenance	140	(4)
Ontology Pruning	140	(2)
Ontology Refinement	142	(2)
Conclusion	144	(7)
Multi-Strategy Learning	145	(1)
Taxonomic vs. Non-Taxonomic Relations	145	(1)
A Note on Learning Axioms --- AO	146	(5)
Part III Implementation & Evaluation
The Text-To-Onto Environment	151	(20)
Component-based Architecture	153	(1)
Ontology Engineering Environment ONTOEDIT	154	(9)
Components for Ontology Learning	163	(5)
Conclusions	168	(3)
Evaluation	171	(32)
The Evaluation Approach	172	(1)
Ontology Comparison Measures	173	(10)
Precision and Recall	174	(1)
Lexical Comparison Level Measures	175	(2)
Conceptual Comparison Level Measures	177	(6)
Human Performance Evaluation	183	(7)
Ontology Engineering Evaluation Study	184	(1)
Human Evaluation -- Precision and Recall	185	(2)
Human Evaluation -- Lexical Comparison Level	187	(1)
Human Evaluation -- Conceptual Comparison Level	188	(2)
Ontology Learning Performance Evaluation	190	(6)
The Evaluation Setting	191	(1)
Evaluation of Lexical Entry Extraction	191	(2)
Evaluation of Concept Hierarchy Extraction	193	(1)
Evaluation of Non-Taxonomic Relation Extraction	194	(2)
Conclusion	196	(7)
Application-oriented Evaluation	197	(1)
Standard Datasets for Evaluation	198	(5)
Part IV Related Work & Outlook
Related Work	203	(20)
Related Work on Ontology Engineering	204	(5)
Related Work on Frameworks of KA & ML	209	(3)
Related Work on Data Import & Processing	212	(2)
Related Work on Algorithms	214	(5)
Related Work on Evaluation	219	(4)
Conclusion & Outlook	223	(5)
Contributions	223	(1)
Insights into Ontology Learning	224	(1)
Unanswered Questions	225	(1)
Future Research	226	(2)
References	228	(14)
Index	242