Supervised learning using modifiers: application in colorimetrics

Summary form only given. We present a method for a learning process that we apply to a colorimetric application. In the application, we associate colours to linguistic expressions and these associations can be changed thanks to our learning process. The method consists of memorizing the meaning of the linguistic expressions according to a learning done thanks to the user. To perform this, we use a graph and some linguistic modifiers (such as /spl bsol/much more", /spl bsol/a bit less", etc.) in order to store the acquired knowledge and its associated nuance. Then, we introduce new operations on linguistic modifiers in order to include an information intensity notion in the graph and to finally restore this intensity to the user in a coherent way. Towards this goal, we employ the notions of mathematical composition and inverse.