Citation

Haw, Su Cheng and Chew, Lit Jie and Kusumo, Dana Sulistyo and Naveen, Palanichamy and Ng, Kok Why (2023) Mapping of extensible markup language-to-ontology representation for effective data integration. IAES International Journal of Artificial Intelligence (IJ-AI), 12 (1). p. 432. ISSN 2089-4872

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Abstract

Extensible markup language (XML) is well-known as the standard for data exchange over the internet. It is flexible and has high expressibility to express the relationship between the data stored. Yet, the structural complexity and the semantic relationships are not well expressed. On the other hand, ontology models the structural, semantic and domain knowledge effectively. By combining ontology with visualization effect, one will be able to have a closer view based on respective user requirements. In this paper, we propose several mapping rules for the transformation of XML into ontology representation. Subsequently, we show how the ontology is constructed based on the proposed rules using the sample domain ontology in University of Wisconsin-Milwaukee (UWM) and mondial datasets. We also look at the schemas, query workload, and evaluation, to derive the extended knowledge from the existing ontology. The correctness of the ontology representation has been proven effective through supporting various types of complex queries in simple protocol and resource description framework query language (SPARQL) language.

Item Type:	Article
Uncontrolled Keywords:	Mapping rules, Mapping scheme, Ontology representation, Semantic relationship, Extensible markup language to ontology
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	31 Jan 2023 07:35
Last Modified:	31 Jan 2023 07:35
URII:	http://shdl.mmu.edu.my/id/eprint/11111

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