Title :
Partitioning of ontologies driven by a structure-based approach
Author :
Amato, F. ; De Santo, A. ; Moscato, V. ; Persia, F. ; Picariello, A. ; Poccia, S.R.
Author_Institution :
Dip. di Ing. Elettr. e Tecnol. dell´Inf., Univ. of Naples “Federico II”, Naples, Italy
Abstract :
In this paper, we propose a novel structure-based partitioning algorithm able to break a large ontology into different modules related to specific topics for the domain of interest. In particular, we leverage the topological properties of the ontology graph and exploit several techniques derived from Network Analysis to produce an effective partitioning without considering any information about semantics of ontology relationships. An automated partitioning tool has been developed and several preliminary experiments have been conducted to validate the effectiveness of our approach with respect to other techniques.
Keywords :
graph theory; ontologies (artificial intelligence); topology; automated partitioning tool; network analysis; ontologies partitioning; ontology graph; ontology relationships; structure-based approach; structure-based partitioning algorithm; topological properties; Ions; Ontologies;
Conference_Titel :
Semantic Computing (ICSC), 2015 IEEE International Conference on
Conference_Location :
Anaheim, CA
DOI :
10.1109/ICOSC.2015.7050827