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A Data Mining Based Approach to Research the Relationship between Kansei and Usability: A Case Study of Mobile Phones

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Artificial Intelligence and Computational Intelligence (AICI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7530))

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Abstract

Kansei and usability are two important aspects that should be considered in product development. In order to design the product that not only meets consumer’s affective needs but also is easy to use, this paper presents a novel approach based on data mining to reveal the relationship between kansei and usability. Firstly, kansei image and usability evaluation indexes were determined. Secondly, within-subjects experimental design was applied to test kansei image, usability, and user’s satisfaction. Finally, association rule and decision tree were utilized to mine the experimental data so as to discover the rules hidden in the data. A case study of mobile phones was conducted based on the proposed method. The results suggest that there is a significant relationship between kansei and usability which together influence user’s satisfaction with product. This approach can provide designers with useful suggestions and solutions for product design.

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© 2012 Springer-Verlag Berlin Heidelberg

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Li, Y., Zhu, L. (2012). A Data Mining Based Approach to Research the Relationship between Kansei and Usability: A Case Study of Mobile Phones. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_4

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  • DOI: https://doi.org/10.1007/978-3-642-33478-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33477-1

  • Online ISBN: 978-3-642-33478-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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