Results 11 to 20 of about 3,434 (243)

Results of the Ontology Alignment Evaluation Initiative 2021 [PDF]

, 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., blind evaluation, open evaluation, or consensus).
Abd, Mina, Algergawy, Alsayed, Amardeilh, Florence, Amini, Reihaneh, Fallatah, Omaima, Faria, Daniel, Fundulaki, Irini, Harrow, Ian, Hertling, Sven, Hitzler, Pascal, Huschka, Martin, Ibanescu, Liliana, Jiménez-Ruiz, Ernesto, Karam, Naouel, Laadhar, Amir, Lambrix, Patrick, Li, Huanyu, Li, Ying, Michel, Franck, Nasr, Engy, Paulheim, Heiko, Pesquita, Catia, Portisch, Jan, Roussey, Catherine, Saveta, Tzanina, Shvaiko, Pavel, Splendiani, Andrea, Trojahn, Cassia, Vataščinová, Jana, Yaman, Beyza, Zamazal, Ondřej, Zhou, Lu   +31 more
core   +18 more sources

Results of the Ontology Alignment Evaluation Initiative 2024 [PDF]

CEUR Workshop Proceedings
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. The OAEI 2024 campaign offered 13 tracks and was attended by 13 participants.
Pour, Mina Abd Nikooie, Algergawy, Alsayed, Blomqvist, Eva, Buche, Patrice, Chen, Jiaoyan, Cotovio, Pedro Giesteira, Coulet, Adrien, Cufi, Julien, Dong, Hang, Faria, Daniel, Ferraz, Lucas, Hertling, Sven, He, Yuan, Horrocks, Ian, Ibanescu, Liliana, Jain, Dr Sarika, Jiménez-Ruiz, Ernesto, Karam, Naouel, Kraus, Felix, Lambrix, Patrick, Li, Huanyu, Li, Ying, Monnin, Pierre, Paulheim, Heiko, Pesquita, Catia, Sharma, Abhisek, Shvaiko, Pavel, Silva, Marta, Sousa, Guilherme, Trojahn, Cassia, Vataščinová, Jana, Yaman, Beyza, Zamazal, Ondrej, Zhou, Lu   +33 more
core   +21 more sources

Results of the Ontology Alignment Evaluation Initiative 2023. [PDF]

, 2023
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. The OAEI 2023 campaign offered 15 tracks and was attended by 16 participants.
Pour, Mina Abd Nikooie, Algergawy, Alsayed, Buche, Patrice, Castro, Leyla Jael, Chen, Jiaoyan, Coulet, Adrien, Cufi, Julien, Dong, Hang, Fallatah, Omaima, Faria, Daniel, Fundulaki, Irini, Hertling, Sven, He, Yuan, Horrocks, Ian, Huschka, Martin, Ibanescu, Liliana, Jain, Dr Sarika, Jiménez-Ruiz, Ernesto, Karam, Naouel, Lambrix, Patrick, Li, Huanyu, Li, Ying, Monnin, Pierre, Nasr, Engy, Paulheim, Heiko, Pesquita, Catia, Saveta, Tzanina, Shvaiko, Pavel, Sousa, Guilherme, Trojahn, Cassia, Vataščinová, Jana, Wu, Mingfang, Yaman, Beyza, Zamazal, Ondrej, Zhou, Lu   +34 more
core   +17 more sources

Results of the ontology alignment evaluation initiative 2019 [PDF]

, 2019
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 (from simple thesauri to expressive OWL ontologies) and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus).
Algergawy, Alsayed, Faria, Daniel, Ferrara, Alfio, Fundulaki, Irini, Harrow, Ian, Hertling, Sven, Jiménez-Ruiz, Ernesto, Karam, Naouel, Khiat, Abderrahmane, Lambrix, Patrick, Li, Huanyu, Montanelli, Stefano, Paulheim, Heiko, Pesquita, Catia, Saveta, Tzanina, Shvaiko, Pavel, Splendiani, Andrea, Thiéblin, Elodie, Trojahn, Cássia, Vataščinová, Jana, Zamazal, Ondrej, Zhou, Lu   +21 more
core   +11 more sources

Results of the Ontology Alignment Evaluation Initiative 2025. [PDF]

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. The OAEI 2025 campaign offered 12 tracks and was attended by 20 participants.
Abd Nikooie Pour, Mina, Blomqvist, Eva, Giesteira Cotovio, Pedro, Coulet, Adrien, Ferraz, Lucas, Hertling, Sven, Jain, Sarika, Jiménez-Ruiz, Ernesto, Kraus, Felix, Lambrix, Patrick, Li, Huanyu, Li, Ying, Liu, Xianhao, Monnin, Pierre, Paulheim, Heiko, Pesquita, Catia, Sharma, Abhisek, Shvaiko, Pavel, Silva, Marta, Sousa, Guilherme, Trojahn, Cassia, Vataščinová, Jana, Yaman, Beyza, Zamazal, Ondrej, Zhou, Lu   +24 more
core   +11 more sources

Results of the ontology alignment evaluation initiative 2018 [PDF]

, 2018
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 (from simple thesauri to expressive OWL ontologies) and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus).
Algergawy, Alsayed, Cheatham, Michelle, Faria, Daniel, Ferrara, Alfio, Fundulaki, Irini, Harrow, Ian, Hertling, Sven, Jiménez-Ruiz, Ernesto, Karam, Naouel, Khiat, Abderrahmane, Lambrix, Patrick, Li, Huanyu, Montanelli, Stefano, Paulheim, Heiko, Pesquita, Catia, Saveta, Tzanina, Schmidt, Daniela, Shvaiko, Pavel, Splendiani, Andrea, Thiéblin, Elodie, Trojahn, Cássia, Vataščinová, Jana, Zamazal, Ondrej, Zhou, Lu   +23 more
core   +9 more sources

Integrating Sensor Ontologies with Niching Multi-Objective Particle Swarm Optimization Algorithm

Sensors, 2023
Sensor ontology provides a standardized semantic representation for information sharing between sensor devices. However, due to the varied descriptions of sensor devices at the semantic level by designers in different fields, data exchange between sensor
Yucheng Zhuang, Yikun Huang, Wenyu Liu
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

A Compact Brain Storm Algorithm for Matching Ontologies

IEEE Access, 2020
An ontology can formally present the domain knowledge by specifying the domain concepts and their relationships, which is a kernel technique for addressing the data heterogeneity issue in the semantic web. However, since existing ontologies are developed
Xingsi Xue, Jiawei Lu
doaj   +1 more source

Efficient Ontology Meta-Matching Based on Interpolation Model Assisted Evolutionary Algorithm

Mathematics, 2022
Ontology is the kernel technique of the Semantic Web (SW), which models the domain knowledge in a formal and machine-understandable way. To ensure different ontologies’ communications, the cutting-edge technology is to determine the heterogeneous entity ...
Xingsi Xue, Qi Wu, Miao Ye, Jianhui Lv
doaj   +1 more source