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Incremental Ontology Population and Enrichment through Semantic-based Text Mining: An Application for IT Audit Domain

Authors:

Andrea KoAuthors Info & Claims

International Journal on Semantic Web & Information Systems, Volume 11, Issue 3

Pages 44 - 66

https://doi.org/10.4018/IJSWIS.2015070103

Published: 01 July 2015 Publication History

Abstract

Higher education and professional trainings often apply innovative e-learning systems, where ontologies are used for structuring domain knowledge. To provide up-to-date knowledge for the students, ontology has to be maintained regularly. It is especially true for IT audit and security domain, because technology is changing fast. However manual ontology population and enrichment is a complex task that require professional experience involving a lot of efforts. The authors' paper deals with the challenges and possible solutions for semi-automatic ontology enrichment and population. ProMine has two main contributions; one is the semantic-based text mining approach for automatically identifying domain-specific knowledge elements; the other is the automatic categorization of these extracted knowledge elements by using Wiktionary. ProMine ontology enrichment solution was applied in IT audit domain of an e-learning system. After ten cycles of the application ProMine, the number of automatically identified new concepts are tripled and ProMine categorized new concepts with high precision and recall.

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Cited By

Abdoune RLazib LDahmani-Bouarab FFernández-Breis J(2024)ONTO-TDM domain ontology population for a specific disciplineApplied Ontology10.3233/AO-23003619:3(265-285)Online publication date: 22-Oct-2024
https://dl.acm.org/doi/10.3233/AO-230036
Kardan AJafarpour H(2018)N-Dimensional Matrix-Based OntologyInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.201804010314:2(47-69)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.4018/IJSWIS.2018040103
Kő AGillani S(2016)Research Challenges of ICT for Governance and Policy Modelling Domain – A Text Mining-Based ApproachElectronic Government and the Information Systems Perspective10.1007/978-3-319-44159-7_13(182-193)Online publication date: 5-Sep-2016
https://dl.acm.org/doi/10.1007/978-3-319-44159-7_13
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Published In

cover image International Journal on Semantic Web & Information Systems

International Journal on Semantic Web & Information Systems Volume 11, Issue 3

July 2015

66 pages

ISSN:1552-6283

EISSN:1552-6291

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IGI Global

United States

Publication History

Published: 01 July 2015

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Cited By

Abdoune RLazib LDahmani-Bouarab FFernández-Breis J(2024)ONTO-TDM domain ontology population for a specific disciplineApplied Ontology10.3233/AO-23003619:3(265-285)Online publication date: 22-Oct-2024
https://dl.acm.org/doi/10.3233/AO-230036
Kardan AJafarpour H(2018)N-Dimensional Matrix-Based OntologyInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.201804010314:2(47-69)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.4018/IJSWIS.2018040103
Kő AGillani S(2016)Research Challenges of ICT for Governance and Policy Modelling Domain – A Text Mining-Based ApproachElectronic Government and the Information Systems Perspective10.1007/978-3-319-44159-7_13(182-193)Online publication date: 5-Sep-2016
https://dl.acm.org/doi/10.1007/978-3-319-44159-7_13
Molnár BBéleczki ABenczúr A(2016)Application of Legal Ontologies Based Approaches for Procedural Side of Public AdministrationElectronic Government and the Information Systems Perspective10.1007/978-3-319-44159-7_10(135-149)Online publication date: 5-Sep-2016
https://dl.acm.org/doi/10.1007/978-3-319-44159-7_10

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