Ontology Learning for the Semantic Web

2002
ISBN: 978-0-7923-7656-9
Verlag: Springer US

Buch, Englisch, Band 665, 244 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1250 g

Reihe: The Springer International Series in Engineering and Computer Science

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.

Zielgruppe

Research

Autoren/Hrsg.

Maedche, Alexander

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein EDV & Informatik: Ausbildung & Berufe
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Zeichen- und Zahlendarstellungen
• Mathematik | Informatik EDV | Informatik Technische Informatik Hochleistungsrechnen, Supercomputer
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten

Inhaltsverzeichnis

I Fundamentals.- 1. Introduction.- 2. Ontology — Definition & Overview.- 3. Layered Ontology Engineering.- II Ontology Learning for the Semantic Web.- 4. Ontology Learning Framework.- 5. Data Import & Processing.- 6. Ontology Learning Algorithms.- III Implementation & Evaluation.- 7. The TEXT-TO-ONTO Environment.- 8. Evaluation.- IV Related Work & Outlook.- 9. Related Work.- 10. Conclusion & Outlook.- References.