Results 11 to 20 of about 318 (125)

Using NSGA-III for optimising biomedical ontology alignment

open access: yesCAAI 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
doaj   +2 more sources

Optimizing Biomedical Ontology Alignment through a Compact Multiobjective Particle Swarm Optimization Algorithm Driven by Knee Solution

open access: yesDiscrete 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
doaj   +2 more sources

Interactive biomedical ontology matching. [PDF]

open access: yesPLoS ONE, 2019
Due to continuous evolution of biomedical data, biomedical ontologies are becoming larger and more complex, which leads to the existence of many overlapping information.
Xingsi Xue, Zhi Hang, Zhengyi Tang
doaj   +2 more sources

Using Compact Coevolutionary Algorithm for Matching Biomedical Ontologies. [PDF]

open access: yesComput 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

Ontology Alignment Architecture for Semantic Sensor Web Integration [PDF]

open access: yesSensors, 2013
Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc.
Bernardo Alarcos   +3 more
doaj   +2 more sources

Results of the Ontology Alignment Evaluation Initiative 2021 [PDF]

open access: yes, 2021
The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities (e.g ...
Vatascinová, Jana,   +31 more
core   +5 more sources

Multimatcher Model to Enhance Ontology Matching Using Background Knowledge

open access: yesInformation, 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
doaj   +1 more source

Hybridizing Fuzzy String Matching and Machine Learning for Improved Ontology Alignment

open access: yesFuture 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
doaj   +1 more source

An ontology matching approach for semantic modeling: A case study in smart cities

open access: yesComputational 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

Solving Ontology Metamatching Problem through Improved Multiobjective Particle Swarm Optimization Algorithm

open access: yesWireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022
In recent years, knowledge representation in the Artificial Intelligence (AI) domain is able to help people understand the semantics of data and improve the interoperability between diverse knowledge‐based applications. Semantic Web (SW), as one of the methods of knowledge representation, is the new generation of World Wide Web (WWW), which integrates ...
Yikun Huang   +3 more
wiley   +1 more source

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