C4.5: programs for machine learning
C4.5: programs for machine learning
Friendly information retrieval through adaptive restructuring of information space
New Generation Computing - Special issue on real world computing project
Friendly information retreival through adaptive restructuring of information space
IEA/AIE '00 Proceedings of the 13th international conference on Industrial and engineering applications of artificial intelligence and expert systems: Intelligent problem solving: methodologies and approaches
Feature Extraction, Construction and Selection: A Data Mining Perspective
Feature Extraction, Construction and Selection: A Data Mining Perspective
General Model of Subjective Interpretation for Street Landscape Image
DEXA '98 Proceedings of the 9th International Conference on Database and Expert Systems Applications
Color image quantization for frame buffer display
SIGGRAPH '82 Proceedings of the 9th annual conference on Computer graphics and interactive techniques
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In this paper, we apply the algorithms to facilitate learning to kansei modeling and experimentally investigate constructed kansei model itself. We introduce using a vector space as a scheme of the mental representation and place still images in the perceptual space by generating perceptual features. Furthermore we propose a method to manipulate the perceptual data by optimizing modeling parameters based on the kansei scale. After this adaptation we compare the similarity between the kansei clusters using their distance in the space to evaluate if the adapting perceptual space is appropriate for one's kansei. We have conducted preliminary experiments utilizing image data of TV commercials and briefly evaluated the mental space constructed by our method through the kansei questionnaire.