Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
