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논문검색

An Emotional Space Modeling for the Adaptive Emotional Model Design Based on Sugeno Fuzzy Inference

초록

영어

To maximize the quality improvement and tangibility of emotion-based personalized services, a lot of efforts are put into researches on emotional expression languages, measurement of emotions, emotional transference and expression model, personalized emotional space model, emotion-based personalized services, and so forth. To maximize quality improvement and tangibility of emotion-based personalized services, research on emotional modeling for quantitative and structural expression of human emotions needs to precede the others. In addition, a high level of inference on human emotions as well as an emotional model with learning capabilities is necessary for personalized emotion modeling.
To this end, this study defines the 12 emotional expression languages, which are defined in Thayer’s Valence-Arousal emotion model, with the fuzzy membership function. For emotional transference and inference modeling based on valence and arousal input, Mamdani and Sugeno Fuzzy Inference Methods are applied and evaluated. In this manner, this study provides the basis for an adaptive emotional inference system based on the personalized emotional model and neuro-fuzzy system required for personalized services.

목차

Abstract
 1. Introduction
 2. Related Studies
  2.1. Fuzzy and Fuzzy Inference System
  2.2. Thayer Emotional Space Model
 3. FIS-based Emotional Space Establishment and Inference
  3.1. Emotional Space Modeling Steps and Methods
  3.2. Design of the Fuzzy Inference System Based on the Emotional Model
  3.3. Definition of the Input/Output Fuzzy Set
  3.4. Definition of Inference Rules and Inference Methods
 4. Experiment and Evaluation
 5. Conclusion
 Acknowledgements
 References

저자정보

  • Il-Kyoung Kwon Dept. of computer Science & Engineering, Kongju National University
  • Sang-Yong Lee Div. of Computer Science & Engineering, Kongju National University

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