MindMapping  is a well-known technique used in note taking and is known to encourage learning and studying. Besides, MindMapping can be a very good way to present knowledge and concepts in a visual form. Unfortunately there is no reliable automated tool that can generate MindMaps from Natural Language text. This paper fills in this gap by developing the first evaluated automated system that takes a text input and generates a MindMap visualization out of it. The system also could visualize large text documents in multilevel MindMaps in which a high level MindMap node could be expanded into child MindMaps. The proposed approach involves understanding of the input text converting it into intermediate Detailed Meaning Representation (DMR). The DMR is then visualized with two proposed approaches; Single level or Multiple levels which is convenient for larger text. The generated MindMaps from both approaches were evaluated based on Human Subject experiments performed on Amazon Mechanical Turk with various parameter settings. © 2012 IEEE.
|Original language||English (US)|
|Title of host publication||Proceedings - 2012 IEEE International Symposium on Multimedia, ISM 2012|
|State||Published - Dec 1 2012|