Incremental Ontology Population and Enrichment through Semantic-based Text Mining

Author:

Gillani Saira1,Ko Andrea1

Affiliation:

1. Corvinus University of Budapest, Budapest, Hungary

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.

Publisher

IGI Global

Subject

Computer Networks and Communications,Information Systems

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Security Ontology Structure for Formalization of Security Document Knowledge;Electronics;2022-03-31

2. Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies;Computer Systems Science and Engineering;2022

3. NLPHub: An e‐Infrastructure‐based text mining hub;Concurrency and Computation: Practice and Experience;2020-09-09

4. Ontology Applications in E-Learning Systems;2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI);2020-06

5. Two Ways for the Automatic Generation of Application Ontologies by Using BalkaNet;International Journal on Semantic Web and Information Systems;2020-04

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