Detecting duplicate objects in ontologies using FCA
Mikhail Klimushkin, Dmitry Ilvovsky · Automatic Documentation and Mathematical Linguistics · 2013
In our work we consider a new approach to detecting duplicates in an ontology built on real redundant data. This approach is based on the transformation of an initial ontology into a formal context and processing of this context using Formal Concept Analysis (FCA) methods. A new index for measuring the similarity between objects in formal concept analysis is introduced to detect duplicate objects. We study the new approach on a real ontology based on the collection of political news and documents. The proposed index is compared with the existing indices and methods for detecting object similarity.