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Towards a Bottom-up Approach to Data and Knowledge Modeling and Fusion

Chen, Liming, Du, Ying and Wang, Hui (2007) Towards a Bottom-up Approach to Data and Knowledge Modeling and Fusion. In: Workshop on Semantic Web for Collaborative Knowledge Acquisition, in the 20th International Joint Conference on Artificial Intelligence, Hyderabad, India. UNSPECIFIED. 6 pp. [Conference contribution]

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The Web is evolving into a global information and knowledge space that brings huge potentials as well as great challenges. The Semantic Web tries to harness the inter-connected information space by giving information well-defined meaning, but so far failed to deliver its promises. This paper introduces a bottom-up approach to heterogeneous data and knowledge modeling and fusion. The enabling technologies for this approach include the Semantic Web, personalized knowledge portal and social networking. We describe a system architecture that allows individuals to create semantic content in their own desktop with little effort and pool it into a global virtual knowledge base where content can be seamlessly fused and shared. A prototype system is partially developed to illustrate the operation of the approach through which testing and evaluation are conducted.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
Computer Science Research Institute > Smart Environments
ID Code:8731
Deposited By: Dr Liming Chen
Deposited On:09 Mar 2010 12:47
Last Modified:09 May 2016 10:55

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