A proposed structure of human knowledge based on similarity transformations

A theoretical foundation for similarity transformations is presented. The transformations may be used for information reductions and extensions. The technique, using an artificial neural network to reduce information loss in the reduction-extension process is introduced. The process is then applied to model a structure of the human knowledge in both information storage and retrieval. Results of an experiment in recognition photos are used to demonstrate an application of the proposed structure