research-article

Semantic data mining in the information age: : A systematic review

Authors:

Chanmee Sirichanya,

Kesorn KraisakAuthors Info & Claims

International Journal of Intelligent Systems, Volume 36, Issue 8

Pages 3880 - 3916

https://doi.org/10.1002/int.22443

Published: 30 June 2021 Publication History

Abstract

Data mining is the discovery of meaningful information or unrevealed patterns in data. Traditional data‐mining approaches, using statistical calculations, machine learning, artificial intelligence, and database technology, cannot interpret data on a conceptual or semantic level and fail to reveal the meanings within the data. This results in a user not being analyzed and determines its signification and implications. Several semantic data‐mining approaches have been proposed in the past decade that overcome these limitations by using a domain ontology as background knowledge to enable and enhance data‐mining performance. The main contributions of this literature survey include organizing the surveyed articles in a new way that provides ease of understanding for interested researchers, and the provision of a critical analysis and summary of the surveyed articles, identifying the contribution of these papers to the field, and the limitations of the analysis methods and approaches discussed in this corpus, with the intention of informing researchers in this growing field in their innovative approaches to new research. Finally, we identify the future trends and challenges in this study track that will be of concern to future researchers, such as dynamic knowledge‐based methods or big‐data tool collaboration. This survey article provides a comprehensive overview of the literature on domain ontologies as used in the various semantic data‐mining tasks, such as preprocessing, modeling, and postprocessing. We investigated the role of semantic data mining in the field of data science and the processes and methods of applying semantic data mining to a data resource description framework.

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Cited By

Chang TWang S(2024)Semantic Analysis of Vaccine and Online Shopping-Related Stock Forums During the COVID-19 PandemicInternational Journal of Intelligent Systems10.1155/2024/28345442024Online publication date: 1-Jan-2024
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https://dl.acm.org/doi/10.1016/j.aei.2023.102156
Zhao SZhang HZhang XLi WGao FWen Q(2022)Forward privacy multikeyword ranked search over encrypted databaseInternational Journal of Intelligent Systems10.1002/int.2288437:10(7356-7378)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1002/int.22884

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cover image International Journal of Intelligent Systems

International Journal of Intelligent Systems Volume 36, Issue 8

August 2021

852 pages

ISSN:0884-8173

DOI:10.1002/int.v36.8

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© 2021 Wiley Periodicals LLC.

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John Wiley and Sons Ltd.

United Kingdom

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Published: 30 June 2021

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Cited By

Chang TWang S(2024)Semantic Analysis of Vaccine and Online Shopping-Related Stock Forums During the COVID-19 PandemicInternational Journal of Intelligent Systems10.1155/2024/28345442024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/2834544
Chanmee SKesorn K(2023)Semantic decision TreesAdvanced Engineering Informatics10.1016/j.aei.2023.10215658:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.aei.2023.102156
Zhao SZhang HZhang XLi WGao FWen Q(2022)Forward privacy multikeyword ranked search over encrypted databaseInternational Journal of Intelligent Systems10.1002/int.2288437:10(7356-7378)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1002/int.22884

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