A hierarchical model to support Kansei mining process
Image retrieval by subjective content has been recently addressed by the Kansei engineering community in Japan. Such information retrieval systems aim to include subjective aspects of the users in the querying criteria. While many techniques have been proposed in modeling such users' aspects, little attention has been placed on analyzing the amount of information involved in this modeling process and the multi-interpretation of such information. We propose a data warehouse as a support for the mining of the multimedia user feedback. A unique characteristic of our data warehouse lays in its ability to manage multiple hierarchical descriptions of images. Such characteristic is necessary to allow the mining of such data, not only at different levels of abstraction, but also according to multiple interpretation of their content. The proposed data warehouse has been used to support the adaptation of web-based image retrieval systems by impression words. © Springer-Verlag Berlin Heidelberg 2002.