Results 11 to 20 of about 201 (160)

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, Haolin Wang, Jie Zhang, Yikun Huang, Mengting Li, Hai Zhu   +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, Chaofan Yang, Chao Jiang, Pei-Wei Tsai, Guojun Mao, Hai Zhu   +5 more
doaj   +2 more sources

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

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
doaj   +2 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, Ivan Marsa-Maestre, Susel Fernandez, Juan R. Velasco   +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, Wei-Wei Goh, Ee-Xion Tan, Noor Zaman Jhanjhi, Patrice Boursier   +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, Jean Vincent Fonou-Dombeu   +1 more
doaj   +1 more source

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, Hiba Belhadi, Karima Akli‐Astouati, Alberto Cano, Jerry Chun‐Wei Lin   +4 more
wiley   +1 more source

Solving Ontology Metamatching Problem through Improved Multiobjective Particle Swarm Optimization Algorithm

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, Yucheng Zhuang, Xingsi Xue, Yifan Zhu   +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, Junhong Feng, Xishuan Niu, Jian-Hong Wang, Jianhui Lv   +4 more
wiley   +1 more source

Matching Cybersecurity Ontologies on Internet of Everything through Coevolutionary Multiobjective Evolutionary Algorithm

Security and Communication Networks, Volume 2022, Issue 1, 2022., 2022
Since Internet of Everything (IoE) makes all the connections that come online more relevant and valuable, they are subject to numerous security and privacy concerns. Cybersecurity ontology is a shared knowledge model for tackling the security information heterogeneity issue on IoE, which has been widely used in the IoE domain.
Xingsi Xue, Wenbin Tan, Youliang Tian
wiley   +1 more source