Topic Extraction and Extension to Support Concept Mapping

Successful knowledge management may depend not only on knowledge capture, but on knowledge construction—on formulating new and useful knowledge that was not previously available. Electronic concept mapping tools are a promising method for supporting knowledge capture and construction, but users may find it difficult to determine the right knowledge to include. Consequently, knowledge-based methods for suggesting relevant information are desirable for supporting the knowledge modeling process. We are developing methods to aid concept mapping by suggesting relevant information to compare, contrast, and possibly include in knowledge models represented as concept maps. This paper presents two specific methods we are developing for this task, both of which automatically identify topics related to a concept map in order to guide the retrieval of related information. The first, DISCERNER, automatically organizes concept map libraries into a hierarchical structure of topic categories an...

• Type: Conference
• Year: 2003
• Where: FLAIRS
• Authors: David B. Leake, Ana Gabriela Maguitman, Thomas Reichherzer
• Keywords: Artificial Intelligence, Concept Map, Concept Mapping, FLAIRS 2003, Knowledge Capture