Building Integrated Ontological Knowledge Structures with Efficient Approximation Algorithms

Abstract EN

The integration of ontologies builds knowledge structures which brings new understanding on existingterminologies and their associations.

With the steady increase in the number of ontologies, automaticintegration of ontologies is preferable over manual solutions in many applications.

However, availableworks on ontology integration are largely heuristic without guarantees on the quality of the integrationresults.

In this work, we focus on the integration of ontologies with hierarchical structures.

We identifiedoptimal structures in this problem and proposed optimal and efficient approximation algorithms forintegrating a pair of ontologies.

Furthermore, we extend the basic problem to address the integrationof a large number of ontologies, and correspondingly we proposed an efficient approximation algorithmfor integrating multiple ontologies.

The empirical study on both real ontologies and synthetic datademonstrates the effectiveness of our proposed approaches.

In addition, the results of integration betweengene ontology and National Drug File Reference Terminology suggest that our method provides a novelway to perform association studies between biomedical terms.