Towards quick understanding and analysis of large-scale ontologies

Authors:
Miao Xiong;YiFan Chen;Hao Zheng;Yong Yu
Affiliations:
APEX Data and Knowledge Management Lab, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, P.R China;APEX Data and Knowledge Management Lab, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, P.R China;APEX Data and Knowledge Management Lab, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, P.R China;APEX Data and Knowledge Management Lab, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, P.R China
Venue:
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Year:
2006

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Abstract

With the development of semantic web technologies, large and complex ontologies are constructed and applied to many practical applications In order for users to quickly understand and acquire information from these huge information “oceans”, we propose a novel ontology visualization approach accompanied by “anatomies” of classes and properties With the holistic “imaging”, users can both quickly locate the interesting “hot” classes or properties and understand the evolution of the ontology; with the anatomies, they can acquire more detailed information of classes or properties that is arduous to collect by browsing and navigation Specifically, we produce the ontology's holistic “imaging” which contains a semantic layout on classes and distributions of instances Additionally, the evolution of the ontology is illustrated by the changes on the “imaging” Furthermore, detailed anatomies of classes and properties, which are enhanced by techniques in database field (e.g data mining), are ready for users.