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

Liming Chen, Ying Du, Hui Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationUnknown Host Publication
Number of pages6
Publication statusPublished (in print/issue) - Jan 2007
EventWorkshop on Semantic Web for Collaborative Knowledge Acquisition, in the 20th International Joint Conference on Artificial Intelligence - Hyderabad, India
Duration: 1 Jan 2007 → …

Workshop

WorkshopWorkshop on Semantic Web for Collaborative Knowledge Acquisition, in the 20th International Joint Conference on Artificial Intelligence
Period1/01/07 → …

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