Problem Applications Basic techniques Process Conclusions Goals of the tutorial Ontology matching tutorial J´ erˆ ome Euzenat Pavel Shvaiko ◮ Illustrate the role of ontology matching ◮ Provide an overview of basic matching techniques ◮ Demonstrate the use of basic matching techniques in state of the art systems & Montbonnot Saint-Martin, France Trento, Italy ◮ Motivate future research Jerome.Euzenat@inrialpes.fr pavel@dit.unitn.it June 28, 2009 Ontology matching tutorial (v14) – Euzenat and Shvaiko 2 / 51 Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Outline Semantic webs The ontology matching problem 1 Applications 2 Basic techniques 3 Matching process 4 Conclusions 5 Ontology matching tutorial (v14) – Euzenat and Shvaiko 3 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 5 / 51
Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Being serious about the semantic web Living with heterogeneity The semantic web will be: ◮ It is not one guy’s ontology ◮ huge; ◮ It is not several guys’ common ontology ◮ dynamic; ◮ It is many guys and girls’ many ontologies ◮ heterogeneous. ◮ So it is a mess, but a meaningful mess. These are not bugs, they are features. We must learn to live with them. Ontology matching tutorial (v14) – Euzenat and Shvaiko 6 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 7 / 51 Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Heterogeneity problem I have a plan for you Reconciliation can be performed in 2 steps o o ′ Resources being expressed in different ways must be reconciled before being Match, Matcher used. Mismatch between formalized knowledge can occur when: thereby determines the alignment A ◮ different languages are used; ◮ different terminologies are used; Generate Generator ◮ different modelling is used. a processor (for merging, transforming, etc.) Transformation Matching can be achieved at run time or at design time. Ontology matching tutorial (v14) – Euzenat and Shvaiko 8 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 9 / 51
Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Matching process Motivation: two ontologies Monograph Product integer price isbn string title author o parameters doi title uri creator Essay topic A ′ matching A Person Litterary critics DVD Human Politics o ′ resources Book Biography author Writer subject CD Bertrand Russell: My life Autobiography Literature Albert Camus: La chute Ontology matching tutorial (v14) – Euzenat and Shvaiko 10 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 11 / 51 Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Motivation: two ontologies Transformation and mediation ≥ SELECT x.doi SELECT x.isbn Monograph Product WHERE x : Book WHERE x : Autobiography price isbn AND x.author = ”Bertrand Russell” AND x.author = ”Bertrand Russell” title author ≥ AND x.topic = ”Bertrand Russell” doi title creator Essay topic ≥ ≤ Litterary critics Person mediator DVD Human Politics Book Biography author ≥ Writer subject CD Autobiography x.doi=http://dx.doi.org/10.1080/041522862X x.isbn=041522862X Literature Ontology matching tutorial (v14) – Euzenat and Shvaiko 11 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 12 / 51
Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Correspondence Alignment Definition (Correspondence) Given two ontologies o and o ′ , a correspondence between o and o ′ is a Definition (Alignment) 5-uple: � id , e , e ′ , r , n � such that: Given two ontologies o and o ′ , an alignment ( A ) between o and o ′ : ◮ id is an identifier of the correspondence ◮ is a set of correspondences on o and o ′ ◮ e and e ′ are entities of o and o ′ (e.g., XML elements, classes) ◮ with some additional metadata (multiplicity: 1-1, 1-*, method, date, ◮ r is a relation (e.g., equivalence (=), more general ( ⊒ ), disjointness properties, etc.) ( ⊥ )) ◮ n is a confidence measure in some mathematical structure (typically in the [0 1] range) Ontology matching tutorial (v14) – Euzenat and Shvaiko 13 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 14 / 51 Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions An application Interoperability in semantic P2P systems o ′ Matcher query o answer mediator query answer o ′′ Ontology matching tutorial (v14) – Euzenat and Shvaiko 16 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 17 / 51
Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Application: ontology evolution Application: Catalog integration o o ′ Matcher o t o t + n Matcher A A Generator Generator DB Transformation DBPortal Kb t + n Kb t Transformation Ontology matching tutorial (v14) – Euzenat and Shvaiko 18 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 19 / 51 Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Applications: P2P information sharing Applications: Peer-to-peer and emergent semantics o ′ o Matcher o o ′ Matcher o ′ o 1 A 1 A A 1 o 2 o ′ A 2 2 Generator o 3 query query peer1 peer2 mediator peer1 peer2 answer answer Ontology matching tutorial (v14) – Euzenat and Shvaiko 20 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 21 / 51
Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Applications: Web service composition Applications: Agent communication o o ′ Matcher o o ′ Matcher A A Generator Generator axioms service1 mediator service2 message Translator output input Ontology matching tutorial (v14) – Euzenat and Shvaiko 22 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 23 / 51 Problem Applications Basic techniques Process Conclusions Problem Applications Basic techniques Process Conclusions Applications requirements On what basis can we match? ◮ Content: relying on what is inside the ontology automatic operation instances complete run time ◮ Name, comments, alternate names, names of related entities: NLP, IR, correct etc. ◮ Internal structure: constraints on relations, typing Application √ √ √ ◮ External structure: relations between entities: Data mining, Discrete Ontology evolution transformation √ √ √ mathematics Schema integration merging ◮ Extension: Statistics, data analysis, data mining, machine learning √ √ √ Catalog integration data translation ◮ Semantics (models): Reasoning techniques √ √ √ Data integration query answering ◮ Context: the relations of the ontology with the outside √ P2P information sharing query answering ◮ Annotated resources: √ √ √ Web service composition data mediation ◮ The web √ √ √ √ Multi agent communication data translation ◮ External ontologies: dbpedia, etc. √ √ ◮ External resources: wordnet, etc. Query answering query reformulation Ontology matching tutorial (v14) – Euzenat and Shvaiko 24 / 51 Ontology matching tutorial (v14) – Euzenat and Shvaiko 26 / 51
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