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In this sense, NRDR allows the incremental construction of multiple hierarchical ontologies.
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Hierarchical ontologies play a key role in organizing documents in a repository.
In hierarchical ontologies, the concepts are associated with one another only through the "is-a" relation.
We have designed rules that can handle heterogeneities and inconsistencies that are found in hierarchical ontologies.
These rules can be embedded to complement the existing matching systems, to resolve the matching complexities in the hierarchical ontologies.
Finally, we developed the Similarity Search using the combination of a compound graph and hierarchical ontologies.
The Similarity Search using the combination of a graph and hierarchical ontologies is the most unique feature that other databases or ontologies have never achieved.
The hypothesis was tested using multiple hierarchical regression analyses.
Allele frequency in teosinte varied at multiple hierarchical levels.
One common issue in hierarchical ontologies is deciding the level of specificity to use in the analysis [ 65].
For the ODDs, the ontology importing feature was used to build up a hierarchical ontology layer architecture, which can be seen in Figure 1.
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