Structuring and manipulating hand-drawn concept maps

Concept maps are an important tool to knowledge organization, representation, and sharing. Most current concept map tools do not provide full support for hand-drawn concept map creation and manipulation, largely due to the lack of methods to recognize hand-drawn concept maps. We propose a structure recognition method. Our algorithm can extract node blocks and link blocks of a hand-drawn concept map by combining dynamic programming and graph partitioning and then build a concept-map structure by relating extracted nodes and links. We also introduce structure-based intelligent manipulation technique of hand-drawn concept maps. Evaluation shows that our method has high structure recognition accuracy in real time, and the intelligent manipulation technique is efficient and effective. Based on the technique, a note-taking tool `IdeaNote´ is developed. It not only supports natural note taking, but also supports efficient note editing. Besides research related to hand-drawn concept map, I will also introduce our work on other ink computing techniques and the systems we have developed.