Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/8887
Title: Ontology segmentation in ontology matching
Authors: Şentürk, Fatmana
Aytaç, Vecdi
Keywords: Graph
Graph partitioning
Graph segmentation
Ontology matching
Data integration
Semantics
Solvents
Clique percolation
Graph Partitioning
Information discovery
Ontology segmentations
Semantic similarity
Ontology
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Ontologies are domain-specific constructs developed for many different purposes. But, they can be different even within the same domain. Ontology matching is a method for finding the same things in between existing ontologies by looking at semantic similarities. Especially, ontology matching algorithms are used for data integration, reuse of existing ontologies, and information discovery. However, the matching process is quite difficult to perform for large ontologies. For this reason, it is recommended that ontologies can be divided into small pieces and matched modularly. We aim to automatically separate ontologies into sub-segments in this scope of the study. Primarily, the ontology data sets have been converted into a graph structure. Then, We test two algorithms to partition graph. The first algorithm is Karger Algorithm, which finds min-cut edge set in the graph, and the second algorithm is based clique percolation. The test results for both algorithms are shown and the advantages and disadvantages of these two algorithms are explained. © 2017 IEEE.
URI: https://hdl.handle.net/11499/8887
https://doi.org/10.1109/UBMK.2017.8093469
ISBN: 9781538609309
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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