ONTOLOGY-BASED INFORMATION RETRIEVAL USING FUZZY CONCEPT DOCUMENTATION
Been-Chian Chien, Chih-Hung Hu, Ming-Yi Ju
Abstract
Been-Chian Chien, Chih-Hung Hu, Ming-Yi Ju
Abstract
Ontology is a conceptualization of a knowledge domain being shared by a group of users and represented as a machine-readable format. Embedding ontology into information retrieval is a natural way to improve the effectiveness of searching results. In this article, an ontology-based information retrieval framework is proposed to combine the documents retrieval technique with ontology. The ontology used in the system includes a general semantic ontology, domain knowledge, and automatic generated fuzzy concept hierarchy. The experimental results show that a combination of applying different ontologies has a significant impact on the retrieval effectiveness for different query domains.
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Ontology is a conceptualization of a knowledge domain being shared by a group of users and represented as a machine-readable format. Embedding ontology into information retrieval is a natural way to improve the effectiveness of searching results. In this article, an ontology-based information retrieval framework is proposed to combine the documents retrieval technique with ontology. The ontology used in the system includes a general semantic ontology, domain knowledge, and automatic generated fuzzy concept hierarchy. The experimental results show that a combination of applying different ontologies has a significant impact on the retrieval effectiveness for different query domains.
Key concepts: Computer science, Information retrieval, Ontology, Process ontology, Ontology-based data integration, Upper ontology, Suggested Upper Merged Ontology, Ontology Inference Layer