Subjective interpretation of complex data: Requirements for supporting Kansei mining process
Today's technology makes it possible to easily access huge amounts of complex data. As a consequence, techniques are needed for accessing the semantics of such data and supporting the user in selecting relevant information. While meta-languages such as XML have been proposed, they are not suitable for complex data such as images, video, sounds or any other non-verbal channel of communication, because those data have very subjective semantics, i.e., whose interpretation varies over time and between subjects. Yet, providing access to subjective semantics is becoming critical with the significant increase in interactive systems such as web-based systems or socially interactive robots. In this work, we attempt to identify the requirements for providing access to the subjective semantics of complex data. In particular, we focus on how to support the analysis of those dimensions that give rise to multiple subjective interpretations of the data. We propose a data warehouse as a support for the mining process involved. A unique characteristic of the data warehouse lays in its ability to store multiple hierarchical descriptions of the multimedia data. © Springer-Verlag Berlin Heidelberg 2003.