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Information-Flow-based Ontology Mapping

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Information-Flow-based Ontology Mapping Yannis Kalfoglou, University of Southampton Marco Schorlemmer, University of Edinburgh Semantic Web Need the ability to ... – PowerPoint PPT presentation

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Title: Information-Flow-based Ontology Mapping


1
Information-Flow-based Ontology Mapping
  • Yannis Kalfoglou, University of Southampton
  • Marco Schorlemmer, University of Edinburgh

2
Semantic Web
  • Need the ability to automatically
  • MAP ontologies in the same domain
  • MAP ontologies in different domains that overlap
  • MERGE ontologies once they are mapped

3
MAPPING BARRIERS
  • No public technical details available
  • Present systems are so diverse and
    un-interoperable
  • Mapping systems embedded in these diverse systems
  • Previous mapping based on syntactical clues
    instead of semantics
  • Lack theory, axioms, and rules

4
PURPOSE
  • Build mathematics and an algorithm to
    semi-automatically MAP ontologies in RDF

5
OUTLINE
  • Architectural overview
  • Mathematical definitions and proposition
  • IF-map example
  • Basic mapping algorithm
  • Final results
  • Summary
  • My Assessment

6
Architectural Overview
7
IF-map (Information-Flow-Based)
8
Mathematical Definitions and Proposition
  • DEFINITIONS
  • Local Logic
  • Logic Infomorphism
  • Ontology
  • Populated Ontology
  • Ontology Morphism
  • PROPOSITION - Deriving an Ontology Morphism
    relationship from a REFERENCE (unpopulated
    ontology) to a LOCAL (populated ontology)

9
LOCAL LOGICTYPE vehicle carINSTANCE Cabrio
Coupe
10
SYMBOLS
  • T- type, I-instance
  • ? - set of types - disjunctively
  • G - set of types - conjunctively
  • Set of Sequents (G,?)
  • every type, some type

11
LOGIC INFOMORPHISM (f)links 2 local logics (L,
L)f(Coupe) carf(Cabrio) vehicle
12
ONTOLOGY (O)
13
Populated Ontology (?)(Local ontology is
populated with instances x, classifications c
d, and relations r)
14
ONTOLOGY MORPHISMmapping the changeUnpopulated
to Populated
15
MAPPING Architecture
16
ONTOLOGY MORPHISMREFERENCE ONTOLOGY (unpop)to
LOCAL ONTOLOGY (pop)
17
IF-Map ExampleREFERENCE ONTOLOGYunpopulated
18
LOCAL ONTOLOGIES
19
CONSTRAINTS to LOGIC INFORMORPHISMS
20
Relate and Map
21
Relationships between typesREFERENCE - LOCAL
22
Completes ONE MAPPINGf(car) automobile(a)
arity (b) Infomorphism (c) complete
23
Basic Mapping Algorithm
24
Algorithm in Example
  • Match types (MANUALLY?)
  • REFERENCE - building
  • LOCAL - house, cottage
  • Do argument types match semantically?
  • If YES partial map
  • If NO use ISA hierarchy and check parents and
    children and list relations which might be merged

25
FINAL RESULTS (RDF)
26
SUMMARY
  • Formalized definitions, mapping, linking
  • Ontology
  • Ontology morphism
  • Logic Infomorphism
  • FUTURE
  • Ontology Merging
  • Ontology Axioms
  • Reasoning about Ontology Evolution

27
My Assessment
  • Example semantic problem between British
    English and American English (cottage and house)
  • Purpose of the paper changed from the beginning
    to the end WEAK EVALUATION
  • Study of 5 CS Dept in the UK
  • Mathematics and algorithm
  • Hard to tell where Channel Theory left off and
    their Information Flow Theory began
  • RDF Missing technical details of change during
    the IF-map
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