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Xavier Aimé, Orphanet Inserm US14 Jean Charlet, APH-‐HP / Inserm UMR 872 éq20 Francky Trichet, Pascale Kuntz , LINA CNRS Frédéric Fürst , MIS Ferdinand Dhombres, Inserm UMR 872 éq20
Rare Diseases KM: the Contribu3on of Proximity Measurements in OntoOrpha and OMIM
Plan
• Proximity is not similarity • Proxima • OntoOrpha • OMIM corpus • Experiments • Conclusion
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Proximity is not similarity
WordSimilarity-‐353 Test Collec5on : Similarity ( cup , coffee ) ~ 7
• Lev Finkelstein, Evgeniy Gabrilovich, Yossi MaOas, Ehud Rivlin, Zach Solan, Gadi Wolfman, and Eytan Ruppin, "Placing Search in Context:
The Concept Revisited", ACM TransacOons on InformaOon Systems, 20(1):116-‐131, January 2002
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similar close
Proxima • Structure:
• Terms:
• Instances:
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Gestalt Laws of Perceptual Organiza5on A B
-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
Proxima • Structure:
• Terms:
• Instances:
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A B
-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐A-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐B-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
A B ?
Ontology OntoOrpha (1/2)
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h\p://www.orpha.net -‐ 5,914 entries, >12,000 daily visitors, 36 partners countries
Ontology OntoOrpha (2/2)
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Corpus
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hQp://omim.org/ -‐ 26,151 entry
Ques3on 1
• InformaOon retrieval process: – Seman3c network from OntoOrpha – Weigh3ng rela3ons between 2 concepts
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?
Results
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Ques3on 2
• 2 concepts: – similar / close? – rela3on between these concepts? merge concepts? à EvaluaOon of the conceptualizaOon quality
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A B ?
A B
Similarity / Proximity
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Similarity / Proximity
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Merge concepts? Rela3on of specializa3on?
Similarity / Proximity
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Rela3on?
SubclassOf, same class ?
Data and Method
• Sample: – 5,000 random pairs of concepts without direct rela3on – 5,000 random pairs of concepts with direct rela3on
• Proximity: – Proxima (expres) + OntoOrpha + OMIM
• Similarity: – Jaccard (intens) + Jaro-‐Winckler (expres) + OntoOrpha
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Results
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Results
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Pathology – Pathology : • Emery-‐Dreifuss muscular dystrophy • X-‐linked Emery-‐Dreifuss muscular dystrophy hasSubType OK
Results
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Concept – Subconcept : Cardiac septal defect – Atrial septal defect : SubclassOf OK
Results
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Rela3on(s) between concepts OK
Conclusion & Future work
ü -‐ a method to evaluate the quality of a conceptualiza3on -‐ a method to ponderate the rela3ons -‐ two use cases with a measure of proximity
û -‐ dependant of a corpus (and corpus quality) -‐ dependant of the similarity measure -‐ can not be used with all pairs of concepts ( n.(n-‐1)/2 possibili3es)
heurisOcs
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Xavier Aimé, Orphanet Inserm US14 Jean Charlet, APH-‐HP / Inserm UMR 872 éq20 Francky Trichet, Pascale Kuntz , LINA CNRS Frédéric Fürst , MIS Ferdinand Dhombres, Inserm UMR 872 éq20
Rare Diseases KM: the Contribu3on of Proximity Measurements in OntoOrpha and OMIM
