Ontology Learning for the Semantic Web

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.

Sommario

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.

Riassunto

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.

Dettagli sul prodotto

• Autori: Alexander Maedche
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 13.03.2013
• EAN: 9781461353072
• ISBN: 978-1-4613-5307-2
• Pagine: 244
• Dimensioni: 153 mm x 238 mm x 14 mm
• Illustrazioni: XXIII, 244 p.
• Serie: The Springer International Series in Engineering and Computer Science; The Springer International Series in Engineering and Computer Science
• Categorie: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica; B, Artificial Intelligence, Microprocessors, computer science, engineering, Professions, algorithms and data structures, Theory of Computation, Data Structures and Information Theory, Computers, Information theory, Mathematical theory of computation, Data structures (Computer science), Processor Architectures, Information technology: general topics, Computer architecture and logic design, Computer Architecture, The Computing Profession