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Subjective Interpretation of Complex Data: Requirements for Supporting Kansei Mining Process

  • Nadia Bianchi-Berthouze
  • Tomofumi Hayashi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2797)

Abstract

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.

Keywords

Image Retrieval Complex Data Relevance Feedback User Feedback Subjective Interpretation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Nadia Bianchi-Berthouze
    • 1
  • Tomofumi Hayashi
    • 2
  1. 1.Database Systems LabUniversity of AizuAizu WakamatsuJapan
  2. 2.Japan Advanced Institute of Science and TechnologyNomi Gun, Ishikawa-KenJapan

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