Capturing Graphic Design Knowledge from Interactive User Demonstrations

The abundance of layout problems commonly associated with the presentation of visual information on computer displays necessitates that computer systems be incorporated with graphic design knowledge to effectively and intuitively aid users in presenting, customizing, and organizing this form of data. Current methods of encoding such knowledge requires that human designers verbally translate their expertise into a set of programmable rules, frames, cases, or constraints. Computer systems which can be trained to learn the techniques designers use to effectively present visual information, by having a designer demonstrate their application on a working example may provide a more natural means of translating this type of knowledge from its original visual form into the electronic environment, without the necessity to first translate it into a textual representation. This thesis describes a system which uses a machine learning techniqu