| 9 | | This '''experimental''' AlignmentGenerator tries to tackle large scale ontology alignment, for which other approaches fail due to high memory and/or performance requirements. The general idea is a divide and conquer approach, continously aligning a number of parts of the ontologies and joining them it to a single, large alignment. |
| | 9 | This '''experimental''' AlignmentGenerator tries to tackle large scale ontology alignment, for which other approaches fail due to high memory and/or performance requirements. The general idea is a "divide and conquer" approach, continously aligning a number of parts of the ontologies and joining them it to a single, large alignment. |
| | 10 | |
| | 11 | A basic concept, that is used within this approach, is the ''ContextOntology''. It defines a subontology by taking a single class of another ontology, called anchor, and adding all related classes within a certain distance to it. The relation currently used is the subclass realtion, but any other class to class relation could be used just as well. The distance used is to be called context ''depth''. The resulting set of classes is then interpreted as a new (sub)ontology. Every interface method of the original classes could be used, but return sets have to be truncated to the classes that are actually contained in the new ontology. |
| | 12 | |
| | 13 | In this context, a ''Hotspot'' consists of the following attributes: |
| | 14 | * a source, defining a small part of the original ontology to be aligned. Since this expects the ontology data as a PhaseLib:Ontology, special effort has to be taken |
| | 15 | |
| | 16 | The algorithm requires two exchangeable modules, defined by the following interfaces. |
