Results 11 to 20 of about 1,019 (134)
Interactive biomedical ontology matching. [PDF]
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
Automatic background knowledge selection for matching biomedical ontologies. [PDF]
Ontology matching is a growing field of research that is of critical importance for the semantic web initiative. The use of background knowledge for ontology matching is often a key factor for success, particularly in complex and lexically rich domains ...
Daniel Faria +4 more
doaj +2 more sources
Ontology Matching Method Based on Deep Learning and Syntax
Ontology 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, Jiawei Lu
exaly +3 more sources
Ontology Alignment Architecture for Semantic Sensor Web Integration [PDF]
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
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
LogMap Family Participation in the OAEI 2021 [PDF]
We present the participation of LogMap and its variants in the OAEI 2021 campaign. The LogMap project started in January 2011 with the objective of developing a scalable and logic-based ontology matching system.
Jimenez-Ruiz, E.
core +2 more sources
Hybridizing Fuzzy String Matching and Machine Learning for Improved Ontology Alignment
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
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
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
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

