Results 11 to 20 of about 814 (138)
Optimizing Ontology Alignment through Linkage Learning on Entity Correspondences
Complexity, 2021 Data heterogeneity is the obstacle for the resource sharing on Semantic Web (SW), and ontology is regarded as a solution to this problem. However, since different ontologies are constructed and maintained independently, there also exists the ...
Xingsi Xue +5 more
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Using NSGA-III for optimising biomedical ontology alignment
CAAI Transactions on Intelligence Technology, 2019 To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts
Xingsi Xue +3 more
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Optimizing Ontology Alignment through Improved NSGA-II
Discrete Dynamics in Nature and Society, 2020 Over the past decades, a large number of complex optimization problems have been widely addressed through multiobjective evolutionary algorithms (MOEAs), and the knee solutions of the Pareto front (PF) are most likely to be fitting for the decision maker
Yikun Huang, Xingsi Xue, Chao Jiang
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Discrete Dynamics in Nature and Society, 2020 Nowadays, most real-world decision problems consist of two or more incommensurable or conflicting objectives to be optimized simultaneously, so-called multiobjective optimization problems (MOPs).
Xingsi Xue, Xiaojing Wu, Junfeng Chen
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Comparison of ontology alignment systems across single matching task via the McNemar's test
ACM Transactions on Knowledge Discovery From Data, 2018 Ontology alignment is widely-used to find the correspondences between different ontologies in diverse fields.After discovering the alignments,several performance scores are available to evaluate them.The scores typically require the identified alignment ...
Atashin, Amir Ahooye +3 more
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Dealing with uncertain entities in ontology alignment using rough sets [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, 2012 This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2012 IEEE. Personal use of this material is permitted.
Alireza Mousavi +4 more
core +3 more sources
Using Compact Coevolutionary Algorithm for Matching Biomedical Ontologies. [PDF]
Comput Intell Neurosci, 2018 Over the recent years, ontologies are widely used in various domains such as medical records annotation, medical knowledge representation and sharing, clinical guideline management, and medical decision‐making. To implement the cooperation between intelligent applications based on biomedical ontologies, it is crucial to establish correspondences ...
Xue X, Chen J, Chen J, Chen D.
europepmc +2 more sources
Multimatcher Model to Enhance Ontology Matching Using Background Knowledge
Information, 2021 Ontology matching is a rapidly emerging topic crucial for semantic web effort, data integration, and interoperability. Semantic heterogeneity is one of the most challenging aspects of ontology matching.
Sohaib Al-Yadumi +4 more
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Hybridizing Fuzzy String Matching and Machine Learning for Improved Ontology Alignment
Future Internet, 2023 Ontology alignment has become an important process for identifying similarities and differences between ontologies, to facilitate their integration and reuse.
Mohammed Suleiman Mohammed Rudwan +1 more
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An ontology matching approach for semantic modeling: A case study in smart cities
Computational Intelligence, Volume 38, Issue 3, Page 876-902, June 2022., 2022 Abstract This paper investigates the semantic modeling of smart cities and proposes two ontology matching frameworks, called Clustering for Ontology Matching‐based Instances (COMI) and Pattern mining for Ontology Matching‐based Instances (POMI). The goal is to discover the relevant knowledge by investigating the correlations among smart city data based
Youcef Djenouri +4 more
wiley +1 more source