文档介绍：Agenda
Semantic Web and
Machine Learning Tutorial •Introduction
• Foundations of the Semantic Web
• Ontology Learning
• Learning Ontology Mapping
• Semantic Annotation
Steffen Staab Andreas Hotho
ISWeb – Information Knowledge and Data Engineering Group • Using Ontologies
Systems and Semantic Web University of Kassel
University of Koblenz Germany • Applications
Germany
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Syntax is not enough Information Convergence
• Convergence not just in devices, also in “information”
– Your personal information (phone, PDA,…)
Calendar, photo, home page, files…
– Your “professional” life (laptop, desktop, … Grid)
Web site, publications, files, databases, …
– Your “community” contexts (Web)
Hobbies, blogs, fanfic, works…
• The Web teaches us that people will work to share
– How do we CREATE, SEARCH, and BROWSE in the non-text
Andreas based parts of our lives?
• Tel
• E-Mail
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Meaning of Informationen: XML ≠ Meaning, XML = Structure
(or: what it means to be puter)
name < name ναµε>
education <εδυχατιον education >
CV < CVΧς>
work <ωορκ work >
private <<πριϖατε private >>
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Source of Problems (One) Layer Model of the Semantic Web
XML is unspecific:
n No predetermined vocabulary
o No semantics for relationships
Ön& o must be specified upfront
Only possible in close cooperations
– Small, reasonably stable group
– Common interests or authorities
Not possible in the Web or on a broad scale in
general !
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Some Principal Ideas What is an Ontology?
• URI – uniform resource identifiers Gruber 93:
•XML –commonsyntax
• Interlinked An Ontology is a
• Layersof semantics– Tim Berners- formal specification ⇒ Executable
from database to Lee, Weaving of a shared ⇒ Group of persons
knowledge base to the Web
proofs conceptualization ⇒ About concepts
of a domain of interest ⇒ Between application
and „unique truth“
Design principles of antics!!
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Menu Menu
Taxonomy Thesaurus
Object Objec