Results 11 to 20 of about 201 (161)
Matching Transportation Ontologies with Word2Vec and Alignment Extraction Algorithm
Journal of Advanced Transportation, 2021 The development of intelligent transportation systems (ITSs) faces the challenge of integrating data from multiple unrelated sources. As one of the core technologies of knowledge integration in ITS, an ontology typically provides a normative definition ...
Xingsi Xue +5 more
doaj +2 more sources
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
doaj +2 more sources
Ontology Matching Method Based on Deep Learning and Syntax
Big Data and Cognitive ComputingOntology technology addresses data heterogeneity challenges in Internet of Everything (IoE) systems enabled by Cyber Twin and 6G, yet the subjective nature of ontology engineering often leads to differing definitions of the same concept across ontologies,
Changfeng Yan
exaly +3 more sources
Ontology Alignment Architecture for Semantic Sensor Web Integration [PDF]
Sensors, 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
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
doaj +1 more source
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
doaj +1 more source
SANOM Results for OAEI 2019 [PDF]
CoRR, 2019 Information and Communication ...
Mohammadi, Majid (author) +3 more
openaire +4 more sources
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
Wireless 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
Using Competitive Binary Particle Swarm Optimization Algorithm for Matching Sensor Ontologies
Mobile Information Systems, Volume 2022, Issue 1, 2022., 2022 Developing sensor ontologies and using them to annotate the sensor data is a feasible way to address the data heterogeneity issue on Internet of Things (IoT). However, the heterogeneity issue exists between different sensor ontologies hampers their communications. Sensor ontology matching aims at finding all the heterogeneous entities in two ontologies,
Lei Xiao +4 more
wiley +1 more source