2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA) (2016)
March 23, 2016 to March 25, 2016
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AINA.2016.70
Ontology is widely used as a mean to represent and share common concepts and knowledge from a particular domain or specialisation. As a knowledge representation, the knowledge within an ontology must be able to evolve along with the recent changes and updates within the community practice. In this paper, we propose a new Ontology-based Information Extraction (OBIE) system that extends existing systems in order to enrich and validate an ontology. Our model enables the ontology to find related recent knowledge in the domain from communities, by exploiting their underlying knowledge as keywords. The knowledge extraction process uses ontology-based and pattern-based information extraction technique. Not only the extracted knowledge enriches the ontology, it also validates contradictory instance-related statements within the ontology that is no longer relevant to recent practices. We determine a confidence value during the enrichment and validation process to ensure the stability of the enriched ontology. We implement the model and present a case study in herbal medicine domain. The result of the enrichment and validation process shows promising results. Moreover, we analyse how our proposed model contributes to the achievement of a richer and stable ontology.
Ontologies, Information retrieval, Stability analysis, Microwave integrated circuits, Semantics, Feature extraction
D. H. Fudholi, W. Rahayu and E. Pardede, "Ontology-Based Information Extraction for Knowledge Enrichment and Validation," 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), Crans-Montana, Switzerland, 2016, pp. 1116-1123.