Open Access Repository

Automated class correction and enrichment in the Semantic Web

Barati, M, Bai, Q ORCID: 0000-0003-1214-6317 and Liu, Q 2019 , 'Automated class correction and enrichment in the Semantic Web' , Journal of Web Semantics, vol. 59 , pp. 1-18 , doi: 10.1016/j.websem.2019.100533.

Full text not available from this repository.


The Semantic Web is an effort to interchange unstructured data over the Web into a structured format that is processable not only by human beings but also computers. The key backbones of Semantic Web are ontologies and annotations that provide semantics for data. Ontologies are usually created before actual data is populated. Subsequently, they can be incomplete and they often do not provide all aspects that are required for specific domains of knowledge. Additionally, Semantic Web-based ontologies usually suffer from a considerable amount of faulty facts which are known as Semantic Web data quality issues. Due to the complexity of relationships, Semantic Web data quality issues are continuously growing. This paper follows two main objectives. Firstly, it concentrates on a specific Semantic Web data quality issue that indicates incorrect assignment between instances and classes in the ontology. Secondly, the paper shows how to discover new classes which are not defined in the ontology and how to place them in the hierarchical structure of the ontology. To make ends meet, an entropy-based approach called ACE (Automated Class Corrector and Enricher) is proposed that not only evaluates the correctness and incorrectness of relationships between instances and classes but also generates new classes to enrich ontologies. The contributions of ACE have been also explained throughout the paper. Initial experiments conducted on a Semantic Web dataset demonstrate the effectiveness of the ACE.

Item Type: Article
Authors/Creators:Barati, M and Bai, Q and Liu, Q
Keywords: Semantic Web mining, knowledge discovery, ontology, information theory, incorrect class assignment, Semantic Web data quality issues, class enrichment, ontology enrichment
Journal or Publication Title: Journal of Web Semantics
Publisher: Elsevier BV
ISSN: 1570-8268
DOI / ID Number: 10.1016/j.websem.2019.100533
Copyright Information:

©2019 Elsevier B.V. All rights reserved.

Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page