Volume 1 Number 3 (Aug. 2011)
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IJEEEE 2011 Vol.1(3): 193-200 ISSN: 2010-3654
DOI: 10.7763/IJEEEE.2011.V1.30

Adaptive Knowledge Visualization Systems: A Proposal and Implementation

Xiaoyan Bai, David White, and David Sundaram
Abstract—Visualizations are crucial to the creation, transfer and sharing of knowledge. However, there are three essential problems associated with existing knowledge management systems (KMS) and their visualizations. First, KMS tend to provide weak support for leveraging visualization to accomplish transformation, discovery and learning of knowledge. Second, KMS do not possess mechanisms to aid in sensing, analyzing and responding to contextual changes. Third, KMS are weak in adapting to diverse and changing problem and knowledge worker contexts. To address these problems, we propose and implement a contextual adaptive knowledge visualization model and system in this paper. Furthermore, we demonstrate the system implementation through a sequence of scenario-driven illustrations.

Index Terms—knowledge visualization, context, knowledge worker, adaptive, knowledge creation, knowledge sharing, model, implementation.

Xiaoyan Bai, David White, and David Sundaram are with Department of Information Systems and Operations Management, University of Auckland, Auckland, New Zealand.

Cite: Xiaoyan Bai, David White, and David Sundaram, "Adaptive Knowledge Visualization Systems: A Proposal and Implementation," International Journal of e-Education, e-Business, e-Management and e-Learning vol. 1, no. 3, pp. 193-200, 2011.

General Information

ISSN: 2010-3654
Frequency: Quarterly (Since 2015)
Editor-in-Chief: Prof. Kuan-Chou Chen
Executive Editor: Mr. Ron C. Wu
Abstracting/ Indexing: Engineering & Technology Digital Library, Google Scholar, Electronic Journals Library, QUALIS, ProQuest, EI (INSPEC, IET)
E-mail: ijeeee@iap.org
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