Ontology Learning for the Semantic Web

  • Alexander Maedche

Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 665)

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Fundamentals

    1. Front Matter
      Pages 1-1
    2. Alexander Maedche
      Pages 3-10
    3. Alexander Maedche
      Pages 11-27
    4. Alexander Maedche
      Pages 29-55
  3. Ontology Learning for the Semantic Web

    1. Front Matter
      Pages 57-57
    2. Alexander Maedche
      Pages 59-79
    3. Alexander Maedche
      Pages 81-116
    4. Alexander Maedche
      Pages 117-147
  4. Implementation & Evaluation

    1. Front Matter
      Pages 149-149
    2. Alexander Maedche
      Pages 151-170
    3. Alexander Maedche
      Pages 171-199
  5. Related Work & Outlook

    1. Front Matter
      Pages 201-201
    2. Alexander Maedche
      Pages 203-222
    3. Alexander Maedche
      Pages 223-227
  6. Back Matter
    Pages 229-244

About this book

Introduction

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.

Keywords

algorithms evaluation knowledge knowledge discovery learning ontology semantic web

Authors and affiliations

  • Alexander Maedche
    • 1
  1. 1.University of KarlsruheGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-0925-7
  • Copyright Information Kluwer Academic Publishers 2002
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5307-2
  • Online ISBN 978-1-4615-0925-7
  • Series Print ISSN 0893-3405
  • About this book