Semantic retrieval system based on ontology

Authors:
Jianbo Xu;Zhonglin Xu;Jiaxun Chen
Affiliations:
Information College, Donghua University, Shanghai, People's Republic of China;Aviation University of Air Force, People's Republic of China;Information College, Donghua University, Shanghai, People's Republic of China
Venue:
ISP'06 Proceedings of the 5th WSEAS International Conference on Information Security and Privacy
Year:
2006

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Ontology Learning for the Semantic Web

Ontology Learning for the Semantic Web

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Abstract

The recall factor is low when keywords are used to retrieve information, and many related documents are omitted. Semantic annotation is used to comment documents to improve the recall factor. While extremely large instances querying requirements may crash ABox reasoner. In this research, a method is proposed to improve the efficiency of semantic retrieving via combining ABox reasoning and database retrieving. A definition of semantic relatedness between two concepts is proposed by way of computing the semantic distance. In order to avoid repeatedly computing the relatedness in information retrieving, semantic relatedness is computed outline and saved. We note documents with Annotea editing system and extract these annotations to store semantic relatedness information in database. And an algorithm is proposed to retrieve semantic information in database.