Post on 10-Feb-2016
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Result of Ontology Alignment with RiMOM at OAEI’06
Yi Li, Juanzi Li, Duo Zhang, Jie TangKnowledge Engineer Group
Tsinghua UniversityNov. 5th 2006
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OutlineRiMOM PrinciplesProcess
Similarity Factor CalculationMultiple Strategy ExecutionSimilarity PropagationResults refinement
Evaluation ResultsConclusions
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RiMOM -- Risk Minimization based Ontology Mapping
Multiple strategies using different types of linguistic information
Propagation using structural informationStrategy selection for different alignment
tasksRefinement using a priori knowledge
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Processing Flowontologies
O1 O2
Linguistic Strategies
Edit distance
KNN
Alignments Combination
Similarity Propagation
Alignment refinement
mapping
O2
O1
Strategy Selection
Similarity factors estimation
Label Similarity Factor
Structural Similarity Factor
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Multiple Linguistic Strategies
Edit distance on entity’s labelKNN on entity’s description
and instances’ textAdd some structural features
Conferece
Conference
label
The location of an event, An event presenting work
description
Spg04(label:)SemPGrid 04 Workshop(name:)SemPGrid 04 Workshop(location:)New-York NY US(date:)--05 2004
instances
…
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Similarity Propagation
Thing Object
location place
subClassOf
hasProperty range
subClassOf
hasProperty range
Reference Address DirectionsEntry
ThingObject
ReferenceDirections
AddressDirection
ReferenceEntry
AddressEntry
locationplace
subClassOf
hasProperty range
The construction of an intermediate graph from original ontologies
Ontology 1 Ontology 2
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Similarity Propagation (cont.)
Propagate similarities along edgesThree types of edges:
Class to Class (CCP)Class to Property (CPP)Property to Property (PPP)
ThingObject
ReferenceDirections
AddressDirection
ReferenceEntry
AddressEntry
locationplace
subClassOf
hasProperty range
0.7
0.3 0.6 0.5 0.2
0.9
weight=0.5
0.6+0.7*0.5+0.9*0.5=1.4
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Strategy Selection—Similarity factor
Label similarity factor
Structure similarity factor
1 2
# __max(# ,# )same labelF LS
c c
1 2
# __max(# _ ,# _ )
common conceptF SSnonleaf c nonleaf c
Part
Chapter
InBook
InCollection
InProceedings
JournalPart
Article
Review
Editorial
Letter
Part
Chapter
InBook
InCollection
InProceedings
Article
Ontology 1 Ontology 2
F_LS = 6/10
F_SS = 1/2
max(#c1, #c2) = 10max(#nonleaf_c1, #nonleaf_c2) = 2
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Strategy SelectionStrategy Selection
Selection with the two similarity factorsDetermining whether a strategy is to be used in
the alignment processE.g. if F_SS>0.25, we use CCP, CPP, and PPP
for propagation. …Linguistic Strategy
Adding structural features in KNN
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RefinementUsing heuristic rules
Remove the alignments of external and anonymous entities (basic refinement)
Remove “Unbelievable” alignmentsIndistinguishable entities
Pick up 1:1 alignments…
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OutlineRiMOM PrinciplesProcess
Similarity Factor CalculationMultiple Strategy ExecutionSimilarity PropagationResults refinement
Evaluation ResultsConclusions
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Evaluation ResultsBenchmark task
# Precision Recall F-Measure Avg. Time101~104 1.00 1.00 1.000 3.36s201~210 0.98 0.95 0.969 2.638s221~247 0.99 1.00 0.996 1.99s248~266 0.89 0.63 0.736 1.59s301~304 0.83 0.83 0.826 3.14sH-Means 0.96 0.88 0.918 2.18s
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Analysis of the Evaluation ResultsLinguistic (with KNN new features)
P: 0.94 R:0.77Linguistic + Propagation + Refinement
P: 0.89 R: 0.83Our Approach
P: 0.96 R:0.88
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Other Evaluation ResultsFood task
Directory taskPrec: 39.25%, Rec: 40.40%, F: 39.82%
Conference taskPrec: 38%, Rec: 62%
biological & chemical mappings 0.85
taxonomical mappings 0.82
miscellaneous mappings 0.78
all-round 0.81
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ConclusionsImplemented multiple strategies for
ontology alignmentProposed utilizing strategy selection for
different alignment tasksOur approach can improve the accuracy of
ontology alignment effectively
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THANK YOU!http://keg.cs.tsinghua.edu.cn/project/RiMOM