Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5445)
Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (16 chapters)
-
Partitioning and Extraction of Modules
Keywords
About this book
This book constitutes a collection of research achievements mature enough to provide a firm and reliable basis on modular ontologies. It gives the reader a detailed analysis of the state of the art of the research area and discusses the recent concepts, theories and techniques for knowledge modularization.
The 13 papers presented in this book were all carefully reviewed before publication. They have been organized in three parts: Part I gives a general introduction to the idea and issues characterizing modularization and offers an in-depth analysis of properties, criteria and knowledge import techniques for modularization. Part II describes four major research proposals for creating modules from an existing ontology either by partitioning an ontology into a collection of modules or by extracting one or more modules from the ontology. Part III reports on collaborative approaches where modules that pre-exist are linked together through mappings to form a virtual large ontology.
Editors and Affiliations
Bibliographic Information
Book Title: Modular Ontologies
Book Subtitle: Concepts, Theories and Techniques for Knowledge Modularization
Editors: Heiner Stuckenschmidt, Christine Parent, Stefano Spaccapietra
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-642-01907-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2009
Softcover ISBN: 978-3-642-01906-7Published: 25 May 2009
eBook ISBN: 978-3-642-01907-4Published: 17 May 2009
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: X, 378
Topics: Information Systems Applications (incl. Internet), Information Storage and Retrieval, Database Management, Software Engineering, Data Mining and Knowledge Discovery, Data Structures