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

被引:14
作者
Gillani, Saira [1 ]
Ko, Andrea [1 ]
机构
[1] Corvinus Univ Budapest, Budapest, Hungary
关键词
Knowledge Extraction; Information Gain; IT Audit; Ontology Enrichment; Ontology Learning; Ontology Population; Semantics; Text Mining; FEATURE-SELECTION; CONSTRUCTION; WORDNET; ENGLISH;
D O I
10.4018/IJSWIS.2015070103
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
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.
引用
收藏
页码:44 / 66
页数:23
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