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UID:calendar.358826.field_event_date.0@www.wright.edu
DTSTAMP:20260219T203856Z
CREATED:20190425T202429Z
DESCRIPTION:Ph.D. Committee:  Drs. Pascal Hitzler (advisor)\, Michelle Chea
 tham\, TK Prasad\, and Catia Pesquita (University of Lisbon) ABSTRACT:Onto
 logy alignment has been studied for over a decade\, and over that time man
 y alignment systems and methods have been developed by researchers in orde
 r to find simple 1-to-1 equivalence matches between two ontologies. Howeve
 r\, very few alignment systems focus on finding complex correspondences. T
 here are several reasons for this limitation. First\, there are no widely 
 accepted alignment benchmarks that contain such complex relationships. Sec
 ond\, tackling complex alignment is a big challenge that requires experts 
 from different domains to work together to manually generate the alignment
 \, which is extremely time-consuming. Third\, the traditional evaluation m
 etrics like precision\, recall\, and f-measure are not fine-grained enough
  to evaluate the performance of a complex alignment system. Therefore\, it
  becomes a big challenge for many developers to create and evaluate the sy
 stems. In this work\, in order to advance the development of ontology matc
 hing\, we seek to address the problem by first developing potential comple
 x alignment benchmarks from real-world ontologies. The benchmark consists 
 of two ontologies\, the GeoLink Base Ontology (GBO) and the GeoLink Modula
 r Ontology (GMO)\, as well as a manually created reference alignment\, tha
 t was developed in consultation with domain experts from different institu
 tions. The alignment includes 1:1\, 1:n\, and m:n equivalence and subsumpt
 ion correspondences\, and is available in both Expressive and Declarative 
 Ontology Alignment Language (EDOAL) and rule syntax. Then\, we create an a
 utomated complex alignment system based on association rule mining to gene
 rate complex correspondences. Our algorithm can also be used in a semi-aut
 omated fashion to effectively assist users in finding potential complex al
 ignment which they can then validate or edit. In addition\, we evaluate th
 e performance of our algorithm on our benchmark and analyze the results in
  detail to provide the insights of the field in the complex ontology align
 ment. 
DTSTART;TZID=America/New_York:20190429T100000
DTEND;TZID=America/New_York:20190429T120000
LAST-MODIFIED:20190425T221359Z
LOCATION:499 Joshi Research Center
SUMMARY:Ph.D. Dissertation Proposal Defense Towards Complex Ontology Alignm
 ent By Lu Zhou
URL;TYPE=URI:/events/phd-dissertation-proposal-defens
 e-towards-complex-ontology-alignment-lu-zhou
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