Knowledge maps (K-maps) have been recognized as an expressive, efficient and effective way to enhance access and navigation of information in a large knowledge repository. However, its capability is limited by the lack of a way to systematically discover the hidden structure of codified knowledge and compactly visualize the map morphology to improve effective navigation. This paper presents a new hybrid approach to tackle these issues and proposes a layered thematic K-map system. The knowledge objects are firstly categorized and labeled according to their hidden conceptual architecture using a hierarchical self-organizing map network and then thematically navigated through a spatially expandable stacked view with corresponding information. The system is tested with a real-world soil remediation patent corpus with various map topologies. A pair-wise evaluation consisting of clustering performance and usability assessment was conducted. Compared with a typical file/directory view, the results of usability evaluation showed that the proposed system enhances the efficiency of comparison tasks while preserving comparable performance of identification and association tasks.
|Number of pages||12|
|Journal||Journal of Computer Information Systems|
|Publication status||Published - 2008 Dec 1|
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Networks and Communications