In this chapter we describe a method for structure-based ontology partitioning and its implementation that is practically applicable to very large ontologies. We show that a modularization based on structural properties of the ontology only already results in modules that intuitively make sense. The method was used for creating an overview graph for ontologies and for extracting key topics from an ontology that correspond to topics selected by human experts. Because the optimal modularization of an ontology greatly depends on the application it is used for, we implemented the partitioning algorithm in a way that allows for adaption to different requirements. Furthermore this adaption can be performed automatically by specifying requirements of the application. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Stuckenschmidt, H., & Schlicht, A. (2009). Structure-based partitioning of large ontologies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5445 LNCS, pp. 187–210). https://doi.org/10.1007/978-3-642-01907-4_9
Mendeley helps you to discover research relevant for your work.