Reducing the search space in ontology alignment using clustering techniques and topic identification
2015 (English)In: Proceedings of the 8th International Conference on Knowledge Capture, New York: ACM Digital Library, 2015, 21- p.Conference paper (Refereed)
One of the current challenges in ontology alignment is scalability and one technique to deal with this issue is to reduce the search space for the generation of mapping suggestions. In this paper we develop a method to prune that search space by using clustering techniques and topic identification. Further, we provide experiments showing that we are able to generate partitions that allow for high quality alignments with a highly reduced effort for computation and validation of mapping suggestions for the parts of the ontologies in the partition. Other techniques will still be needed for finding mappings that are not in the partition.
Place, publisher, year, edition, pages
New York: ACM Digital Library, 2015. 21- p.
Knowledge representation, data mining, ontology alignment
IdentifiersURN: urn:nbn:se:liu:diva-121838DOI: 10.1145/2815833.2816959ISBN: 978-1-4503-3849-3OAI: oai:DiVA.org:liu-121838DiVA: diva2:859923
8th International Conference on Knowledge Capture
FunderCUGS (National Graduate School in Computer Science)Swedish e‐Science Research CenterEU, FP7, Seventh Framework Programme, FP7-IP-608142