Ontology learning algorithm using weak functions

Ontology is widely used in information retrieval, image processing and other various disciplines. This article discusses how to use machine learning approach to solve the most essential similarity calculation problem in multi-dividing ontology setting. The ontology function is regarded as a combinat...

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Bibliographic Details
Main Authors:	Zhu Linli, Hua Gang, Aslam Adnan
Format:	Article
Language:	English
Published:	De Gruyter 2018-12-01
Series:	Open Physics
Subjects:	ontology similarity measuring ontology mapping machine learning 05.10.-a 02.50.-r
Online Access:	https://doi.org/10.1515/phys-2018-0112

id	doaj-3a048cd668d746609ca4ba62b05377f0
record_format	Article
spelling	doaj-3a048cd668d746609ca4ba62b05377f02021-09-05T13:59:36ZengDe GruyterOpen Physics2391-54712018-12-0116191091610.1515/phys-2018-0112phys-2018-0112Ontology learning algorithm using weak functionsZhu Linli0Hua Gang1Aslam Adnan2School of Computer Engineering, Jiangsu University of Technology, Changzhou, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou, ChinaDepartment of Natural Sciences and Humanities, University of Engineering and Technology, Lahore 54000Lahore, PakistanOntology is widely used in information retrieval, image processing and other various disciplines. This article discusses how to use machine learning approach to solve the most essential similarity calculation problem in multi-dividing ontology setting. The ontology function is regarded as a combination of several weak ontology functions, and the optimal ontology function is obtained by an iterative algorithm. In addition, the performance of the algorithm is analyzed from a theoretical point of view by statistical methods, and several results are obtained.https://doi.org/10.1515/phys-2018-0112ontologysimilarity measuringontology mappingmachine learning05.10.-a02.50.-r
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Zhu Linli Hua Gang Aslam Adnan
spellingShingle	Zhu Linli Hua Gang Aslam Adnan Ontology learning algorithm using weak functions Open Physics ontology similarity measuring ontology mapping machine learning 05.10.-a 02.50.-r
author_facet	Zhu Linli Hua Gang Aslam Adnan
author_sort	Zhu Linli
title	Ontology learning algorithm using weak functions
title_short	Ontology learning algorithm using weak functions
title_full	Ontology learning algorithm using weak functions
title_fullStr	Ontology learning algorithm using weak functions
title_full_unstemmed	Ontology learning algorithm using weak functions
title_sort	ontology learning algorithm using weak functions
publisher	De Gruyter
series	Open Physics
issn	2391-5471
publishDate	2018-12-01
description	Ontology is widely used in information retrieval, image processing and other various disciplines. This article discusses how to use machine learning approach to solve the most essential similarity calculation problem in multi-dividing ontology setting. The ontology function is regarded as a combination of several weak ontology functions, and the optimal ontology function is obtained by an iterative algorithm. In addition, the performance of the algorithm is analyzed from a theoretical point of view by statistical methods, and several results are obtained.
topic	ontology similarity measuring ontology mapping machine learning 05.10.-a 02.50.-r
url	https://doi.org/10.1515/phys-2018-0112
work_keys_str_mv	AT zhulinli ontologylearningalgorithmusingweakfunctions AT huagang ontologylearningalgorithmusingweakfunctions AT aslamadnan ontologylearningalgorithmusingweakfunctions
_version_	1717813280067551232

Ontology learning algorithm using weak functions

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