A K-way spectral partitioning of an ontology for ontology matching

2018 ◽  
Vol 36 (4) ◽  
pp. 643-673 ◽  
Author(s):  
Peter Ochieng ◽  
Swaib Kyanda
Author(s):  
Jean-Baptiste Saulnier ◽  
Izan Le Crom

Located off the Guérande peninsula, SEM-REV is the French maritime facility dedicated to the testing of wave energy converters and related components. Lead by Ecole Centrale de Nantes through the LHEEA laboratory, its aim is to promote research alongside the development of new offshore technologies. To this end, the 1km2, grid-connected zone is equipped with a comprehensive instruments network sensing met-ocean processes and especially waves, with two identical directional Waverider buoys deployed on the site since 2009. For the design of moored floating structures and, a fortiori, floating marine energy converters, the knowledge of the main wave resource — for regular operation — but also extreme conditions — for moorings and device survivability — has to be as precise as possible. Also, the consideration of the multiple wave systems (swell, wind sea) making up the sea state is a key asset for the support of developers before and during the testing phase. To this end, a spectral partitioning algorithm has been implemented which enables the individual characterisation of wave systems, in particular that of their spectral peakedness which is especially addressed in this work. Peakedness has been shown to be strongly related to the groupiness of large waves and is defined here as the standard JONSWAP’s peak enhancement factor γ. Statistics related to this quantity are derived from the measurement network, with a particular focus on the extreme conditions reported on SEM-REV (Joachim storm).


2017 ◽  
Vol 43 ◽  
pp. 1-17 ◽  
Author(s):  
Gábor Bella ◽  
Fausto Giunchiglia ◽  
Fiona McNeill
Keyword(s):  

Author(s):  
Naima El Ghandour ◽  
Moussa Benaissa ◽  
Yahia Lebbah

The Semantic Web uses ontologies to cope with the data heterogeneity problem. However, ontologies become themselves heterogeneous; this heterogeneity may occur at the syntactic, terminological, conceptual, and semantic levels. To solve this problem, alignments between entities of ontologies must be identified. This process is called ontology matching. In this paper, the authors propose a new method to extract alignment with multiple cardinalities using integer linear programming techniques. The authors conducted a series of experiments and compared them with currently used methods. The obtained results show the efficiency of the proposed method.


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