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Learning ontologies
An ontology is a specification of a conceptualization that allows us to represent domain knowledge so that we can share a common understanding, enable reuse, make domain assumptions explicit, and separate domain knowledge from operational knowledge. Ontologies offer reasoning services like consistency checking, subsumption, and query answering that are different from those found in XML and relational databases. OWL ontologies use semantics rather than just syntax to represent knowledge about concepts, individuals, and relationships between them.
Learning ontologies
- 1. Learning Ontologies By Alexander De Leon Feb 9, 2009
- 2. What is anOntology? “An ontology is a specification of a conceptualization” Person Fe le m Ma al e Father Mother John Maria isMarriedTo Subject Domain Conceptualization Specification (part of the world) (Concepts, Objects, Relationships) Ontology
- 3. What is anOntology? Ontologies are also Computational Artifacts (like programs) ∑ ⊨ ... Ontology Inferences or Machine Entailments (Reasoner) INPUT OUTPUT
- 4. What can wedo with Ontologies? Ontologies allow us to represent domain knowledge, so that we can: Share common understanding. Enable reuse. Make domain assumptions explicit. Separate domain knowledge from operational knowledge.
- 5. What can wedo with Ontologies? In information systems, manage of information is separated from the application code. A set of services are require for the application to access the information (e.g. querying) Ontologies offer a different set of information services than those found on XML and RDBMS. Information Application Services component logic
- 6. Reasoning Services in OWL-DL Consistency checking Subsumption Satisfiability Entailment Instance checking Query Answering Others: explanations, approximations, etc.
- 7. Semantics vs. Syntax XML Schema (syntactic constraints): <xs:element name= "ParentOfThree" > ... <xs:element ref= "Child" minOccurs= "3" maxOccurs= "3" /> .... </xs:element> Valid XML Document: Invalid XML Document: <ParentOfThree name= "Aphrodite" > <ParentOfThree name= "Aphrodite" > <Child name= "Eros" /> <Child name= "Eros" /> <Child name= "Phobos" /> </ParentOfThree> <Child name= "Himeros" /> </ParentOfThree>
- 8. Semantics vs. Syntax Ontology Concept: ParentOfThree ≡ Person ⊓ ( = 3 hasChild) Consistent: Also consistent: <ParentOfThree rdf:about="#Aphrodite"> <ParentOfThree rdf:about="#Aphrodite"> <hasChild rdf:resource="#Eros"/> <hasChild rdf:resource="#Eros"/> <ParentOfThree> <hasChild rdf:resource="#Phobos"/> <hasChild rdf:resource="#Himeros"/> <hasChild rdf:resource="#Cupid"/> <ParentOfThree> “Open World Semantics” Lack of “Unique Name Assumption”
- 9. OWL Sublanguages of OWL OWL-Full: OWL vocabulary with syntactic freedom of RDF and no computational guarantees. OWL-DL & OWL-Lite: OWL-Lite Correspondence to Description Logics formalisms. OWL-DL OWL-DL : Maximum expressivity while maintaining computational RDFS / OWL-Full completeness and decidability.
- 10. OWL Sublanguages of OWL OWL-Full: OWL vocabulary with syntactic freedom of RDF and no computational guarantees. OWL-DL & OWL-Lite: Correspondence to Description Logics formalisms. OWL-DL : Maximum expressivity while maintaining computational completeness and decidability.
- 11. OWL Entities of anOWL ontology are identified by URIs (e.g. http://dumontierlab.com/students/alex) The basic entities are: Class (a concept, e.g. Person) Individual (an object, e.g. John) Object Property (a relationship between two individuals, e.g. loves(John, Susan) ) Data Property (an association between an individual an a piece of data, e.g. age(Alex, 26) )