Combining Visual and Textual Modalities for Multimedia Ontology Matching

2011 ◽  
pp. 95-110 ◽  
Author(s):  
Nicolas James ◽  
Konstantin Todorov ◽  
Céline Hudelot
Keyword(s):  
Ontology Matching

Application of Pareto optimization method for ontology matching in nuclear reactor domain

Kerntechnik ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. 678-684
Author(s):  
N. M. Meenachi ◽  
M. Sai Baba
Keyword(s):  
Nuclear Reactor ◽  
Optimization Method ◽  
Pareto Optimization ◽  
Ontology Matching

Incremental, Per-Query Ontology Matching with RepMine

2016 ◽  
Author(s):  
Thomas Kowark ◽  
Keven Richly ◽  
Matthias Uflacker ◽  
Hasso Plattner
Keyword(s):  
Ontology Matching

scholarly journals Language and domain aware lightweight ontology matching

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

Parallelized and distributed task based ontology matching in clustering environment with semantic verification

2017 ◽  
Vol 5 (3) ◽  
pp. 265-279
Author(s):  
Tanni Mittra ◽  
Muhammad Masroor Ali
Keyword(s):  
Ontology Matching

An Integer Linear Programming-Based Method for the Extraction of Ontology Alignment

2021 ◽  
Vol 16 (2) ◽  
pp. 25-44
Author(s):  
Naima El Ghandour ◽  
Moussa Benaissa ◽  
Yahia Lebbah
Keyword(s):  
Linear Programming ◽  
Semantic Web ◽  
Integer Linear Programming ◽  
New Method ◽  
Ontology Matching ◽  
Ontology Alignment ◽  
Programming Techniques ◽  
Data Heterogeneity ◽  
Series Of Experiments

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.

scholarly journals PSOM2—partitioning-based scalable ontology matching using MapReduce

Sadhana ◽  
2017 ◽  
Vol 42 (12) ◽  
pp. 2009-2024 ◽  
Author(s):  
B Sathiya ◽  
T V Geetha ◽  
K Saruladha
Keyword(s):  
Ontology Matching
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