Dynamic mapping of design elements and affective responses: a machine learning based method for affective design

References

• Akay, Diyar, and Mustafa Kurt. 2009. “A Neuro-Fuzzy Based Approach to Affective Design.” The International Journal of Advanced Manufacturing Technology 40 (5-6): 425–437. doi:10.1007/s00170-007-1367-3.
   Web of Science ®Google Scholar
• Bahn, S., C. Lee, C. S. Nam, and M. H. Yun. 2009. “Incorporating Affective Customer Needs for Luxuriousness Into Product Design Attributes.” Human Factors and Ergonomics in Manufacturing & Service Industries 19 (2): 105–127. doi: 10.1002/hfm.20140
   Web of Science ®Google Scholar
• Balducci, F., C. Grana, and R. Cucchiara. 2017. “Affective Level Design for a Role-Playing Videogame Evaluated by a Brain–Computer Interface and Machine Learning Methods.” The Visual Computer 33 (4): 413–427. doi: 10.1007/s00371-016-1320-2
   Web of Science ®Google Scholar
• Barnes, Cathy, and Stephen Paul Lillford. 2009. “Decision Support for the Design of Affective Products.” Journal of Engineering Design 20 (5): 477–492. DOI:doi: 10.1080/09544820902875041.
   Web of Science ®Google Scholar
• Barone, S., A. Lombardo, and P. Tarantino. 2007. “A Weighted Logistic Regression for Conjoint Analysis and Kansei Engineering.” Quality and Reliability Engineering International 23 (6): 689–706. doi: 10.1002/qre.866
   Web of Science ®Google Scholar
• Bhandari, U., T. Neben, K. Chang, and W. Y. Chua. 2017. “Effects of Interface Design Factors on Affective Responses and Quality Evaluations in Mobile Applications.” Computers in Human Behavior 72: 525–534. doi: 10.1016/j.chb.2017.02.044
   Web of Science ®Google Scholar
• Breiman, L., J. H. Friedman, R. A. Olshen, and C. J. Stone. 1984. Classification and Regression Trees. Boca Raton, Florida: CRC press.
   Google Scholar
• Chou, Jyh-Rong. 2016. “A Kansei Evaluation Approach Based on the Technique of Computing with Words.” Advanced Engineering Informatics 30 (1): 1–15. DOI:doi: 10.1016/j.aei.2015.11.001.
   Web of Science ®Google Scholar
• Cortes, C., and V. Vapnik. 1995. “Support-vector Networks.” Machine Learning 20 (3): 273–297.
   Web of Science ®Google Scholar
• Fung, Chris K. Y., C. K. Kwong, Kit Yan Chan, and H. Jiang. 2014. “A Guided Search Genetic Algorithm Using Mined Rules for Optimal Affective Product Design.” Engineering Optimization 46 (8): 1094–1108. DOI:doi: 10.1080/0305215x.2013.823196.
   Web of Science ®Google Scholar
• Fung, K. Y., C. K. Kwong, K. W. M. Siu, and K. M. Yu. 2012. “A Multi-Objective Genetic Algorithm Approach to Rule Mining for Affective Product Design.” Expert Systems with Applications 39 (8): 7411–7419. doi:doi: 10.1016/j.eswa.2012.01.065.
   Web of Science ®Google Scholar
• Guo, Fu, Wei Lin Liu, Yaqin Cao, Fan Tao Liu, and Mei Lin Li. 2016. “Optimization Design of a Webpage Based on Kansei Engineering.” Human Factors and Ergonomics in Manufacturing & Service Industries 26 (1): 110–126. DOI:doi: 10.1002/hfm.20617.
   Web of Science ®Google Scholar
• Hsiao, Y. H., M. C. Chen, and W. C. Liao. 2017. “Logistics Service Design for Cross-Border E-Commerce Using Kansei Engineering with Text-Mining-Based Online Content Analysis.” Telematics and Informatics 34 (4): 284–302. doi:doi: 10.1016/j.tele.2016.08.002.
   Web of Science ®Google Scholar
• Hsu, S. H., M. C. Chuang, and C. C. Chang. 2000. “A Semantic Differential Study of Designers” and Users” Product Form Perception.” International Journal of Industrial Ergonomics 25 (4): 375–391. doi: 10.1016/S0169-8141(99)00026-8
   Web of Science ®Google Scholar
• Jiang, Huimin, C. K. Kwong, Y. Liu, and W. H. Ip. 2014. “A Methodology of Integrating Affective Design with Defining Engineering Specifications for Product Design.” International Journal of Production Research 53 (8): 2472–2488. DOI:doi: 10.1080/00207543.2014.975372.
   Web of Science ®Google Scholar
• Jiang, Huimin, C. K. Kwong, K. W. M. Siu, and Y. Liu. 2015. “Rough set and PSO-Based ANFIS Approaches to Modeling Customer Satisfaction for Affective Product Design.” Advanced Engineering Informatics 29 (3): 727–738. DOI:doi: 10.1016/j.aei.2015.07.005.
   Web of Science ®Google Scholar
• Jiao, J. R., Y. Zhang, and M. Helander. 2006. “A Kansei Mining System for Affective Design.” Expert Systems with Applications 30 (4): 658–673. doi: 10.1016/j.eswa.2005.07.020
   Web of Science ®Google Scholar
• Khalid, Halimahtun M. 2006. “Embracing Diversity in User Needs for Affective Design.” Applied Ergonomics 37 (4): 409–418. DOI:doi: 10.1016/j.apergo.2006.04.005.
   PubMed Web of Science ®Google Scholar
• Kwong, C. K., K. Y. Fung, H. Jiang, K. Y. Chan, and K. W. Siu. 2013. “A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design.” Scientific World Journal 2013: 636. doi:doi: 10.1155/2013/636948.
   Google Scholar
• Kwong, C. K., Huimin Jiang, and Xiaochuan Luo. 2016. “AI-based Methodology of Integrating Affective Design, Engineering, and Marketing for Defining Design Specifications of new Products.” Engineering Applications of Artificial Intelligence 47: 49–60. doi: 10.1016/j.engappai.2015.04.001
   Web of Science ®Google Scholar
• Lai, Hsin-Hsi, Yang-Cheng Lin, Chung-Hsing Yeh, and Chien-Hung Wei. 2006. “User-oriented Design for the Optimal Combination on Product Design.” International Journal of Production Economics 100 (2): 253–267. DOI:doi: 10.1016/j.ijpe.2004.11.005.
   Web of Science ®Google Scholar
• Lin, Yang-Cheng, Hsin-Hsi Lai, and Chung-Hsing Yeh. 2007. “Consumer-oriented Product Form Design Based on Fuzzy Logic: A Case Study of Mobile Phones.” International Journal of Industrial Ergonomics 37 (6): 531–543. DOI:doi: 10.1016/j.ergon.2007.03.003.
   Web of Science ®Google Scholar
• Lin, H. C. K., S. H. Su, C. J. Chao, C. Y. Hsieh, and S. C. Tsai. 2016. “Construction of Multi-Mode Affective Learning System: Taking Affective Design as an Example.” Journal of Educational Technology & Society 19 (2): 132–147.
   Web of Science ®Google Scholar
• Lin, Y. C., and C. C. Wei. 2017. “A Hybrid Consumer-Oriented Model for Product Affective Design: An Aspect of Visual Ergonomics.” Human Factors and Ergonomics in Manufacturing & Service Industries 27 (1): 17–29. doi: 10.1002/hfm.20403
   Web of Science ®Google Scholar
• Lin, Li, Ming-Qing Yang, Jing Li, and Yan Wang. 2012. “A Systematic Approach for Deducing Multi-Dimensional Modeling Features Design Rules Based on User-Oriented Experiments.” International Journal of Industrial Ergonomics 42 (4): 347–358. DOI:doi: 10.1016/j.ergon.2012.03.005.
   Web of Science ®Google Scholar
• Llinares, Carmen, and Alvaro Page. 2007. “Application of Product Differential Semantics to Quantify Purchaser Perceptions in Housing Assessment.” Building and Environment 42 (7): 2488–2497. DOI:doi: 10.1016/j.buildenv.2006.06.012.
   Web of Science ®Google Scholar
• Llinares, Carmen, and Alvaro F. Page. 2011. “Kano’s Model in Kansei Engineering to Evaluate Subjective Real Estate Consumer Preferences.” International Journal of Industrial Ergonomics 41 (3): 233–246. DOI:doi: 10.1016/j.ergon.2011.01.011.
   Web of Science ®Google Scholar
• Lu, W., and J. F. Petiot. 2014. ““Affective Design of Products Using an Audio-Based Protocol: Application to Eyeglass Frame.” “ International Journal of Industrial Ergonomics 44 (3): 383–394. doi: 10.1016/j.ergon.2014.01.004
   Web of Science ®Google Scholar
• Mondragón, Salvador, Pedro Company, and Margarita Vergara. 2005. “Semantic Differential Applied to the Evaluation of Machine Tool Design.” International Journal of Industrial Ergonomics 35 (11): 1021–1029. DOI:doi: 10.1016/j.ergon.2005.05.001.
   Web of Science ®Google Scholar
• Nagamachi, Mitsuo. 1995. “Kansei Engineering: A new Ergonomic Consumer-Oriented Technology for Product Development.” International Journal of Industrial Ergonomics 15 (1): 3–11. doi: 10.1016/0169-8141(94)00052-5
   Web of Science ®Google Scholar
• Nagamachi, M. 1996. Introduction of Kansei Engineering. Tokyo: Japan Standard Association.
   Google Scholar
• Nagamachi, M. 1997. “Kansei Engineering as Consumer-Oriented Ergonomic Technology of Product Development.” In Proceedings of the 13th triennial congress of the international ergonomics association (Vol. 2, pp. 228-230).
   Google Scholar
• Nagamachi, M. 1997. “Kansei Engineering: The Framework and Methods.” Kansei Engineering 1997: 1–9.
   Google Scholar
• Nagamachi, M. 2002. “Kansei Engineering as a Powerful Consumer-Oriented Technology for Product Development.” Applied Ergonomics 33 (3): 289–294. doi: 10.1016/S0003-6870(02)00019-4
   PubMed Web of Science ®Google Scholar
• Nagamachi, M. 2002. “Kansei Engineering in Consumer Product Design.” Ergonomics in Design 10 (2): 5–9. doi: 10.1177/106480460201000203
   Google Scholar
• Nagamachi, M., and A. M. Lokman. 2016. Innovations of Kansei Engineering. Boca Raton, Florida: CRC Press.
   Google Scholar
• Osgood, E. C., G. J. Suci, and P. H. Tannenbaum. 1957. The Measurement of Meaning. Urbana, Illinois: University of Illinois Press.
   Google Scholar
• Othman, R., R. Belkaroui, and R. Faiz. 2017. “Extracting Product Features for Opinion Mining Using Public Conversations in Twitter.” Procedia Computer Science 112: 927–935. doi: 10.1016/j.procs.2017.08.122
   Google Scholar
• Park, Jungchul, and Sung H. Han. 2004. “A Fuzzy Rule-Based Approach to Modeling Affective User Satisfaction Towards Office Chair Design.” International Journal of Industrial Ergonomics 34 (1): 31–47. DOI:doi: 10.1016/j.ergon.2004.01.006.
   Web of Science ®Google Scholar
• Rosler, F., G. Battenberg, and F. Schüttler. 2009. “Subjective Perceptions and Objective Characteristics of Control Elements.” ATZautotechnology 9: 48–53.
   Google Scholar
• Schütte*, S. T., J. Eklund, J. R. Axelsson, and M. Nagamachi. 2004. “Concepts, Methods and Tools in Kansei Engineering.” Theoretical Issues in Ergonomics Science 5 (3): 214–231. doi: 10.1080/1463922021000049980
   Google Scholar
• Shieh, M. D., Y. E. Yeh, and C. L. Huang. 2016. “Eliciting Design Knowledge From Affective Responses Using Rough Sets and Kansei Engineering System.” Journal of Ambient Intelligence and Humanized Computing 7 (1): 107–120. doi: 10.1007/s12652-015-0307-6
   Web of Science ®Google Scholar
• Smith, Shana, and Shih-Hang Fu. 2011. “The Relationships Between Automobile Head-up Display Presentation Images and Drivers” Kansei.” Displays 32 (2): 58–68. DOI:doi: 10.1016/j.displa.2010.12.001.
   Web of Science ®Google Scholar
• Vieira, J., J. M. Osorio, S. Mouta, P. Delgado, A. Portinha, J. F. Meireles, and J. A. Santos. 2017. “Kansei Engineering as a Tool for the Design of in-Vehicle Rubber Keypads.” Applied Ergonomics 61: 1–11. DOI:doi: 10.1016/j.apergo.2016.12.019.
   PubMed Web of Science ®Google Scholar
• Wang, W. M., Z. Li, Layne Liu, Z. G. Tian, and Eric Tsui. 2018. “Mining of Affective Responses and Affective Intentions of Products From Unstructured Text.” Journal of Engineering Design 2018. doi:doi: 10.1080/09544828.2018.1448054.
   Google Scholar
• Wang, C. H., and H. C. K. Lin. 2018. “Emotional Design Tutoring System Based on Multimodal Affective Computing Techniques.” International Journal of Distance Education Technologies (IJDET) 16 (1): 103–117. doi: 10.4018/IJDET.2018010106
   Web of Science ®Google Scholar
• Wright, Kevin B. 2005. “Researching Internet-Based Populations: Advantages and Disadvantages of Online Survey Research, Online Questionnaire Authoring Software Packages, and Web Survey Services.” Journal of Computer-Mediated Communication 10 (3): 19–23. doi: 10.1111/j.1083-6101.2005.tb00259.x
   Web of Science ®Google Scholar
• Yan, Hong-Bin, Van-Nam Huynh, Tetsuya Murai, and Yoshiteru Nakamori. 2008. “Kansei Evaluation Based on Prioritized Multi-Attribute Fuzzy Target-Oriented Decision Analysis.” Information Sciences 178 (21): 4080–4093. DOI:doi: 10.1016/j.ins.2008.06.023.
   Web of Science ®Google Scholar
• Zhai, Lian-Yin, Li-Pheng Khoo, and Zhao-Wei Zhong. 2009. “A Rough set Based Decision Support Approach to Improving Consumer Affective Satisfaction in Product Design.” International Journal of Industrial Ergonomics 39 (2): 295–302. DOI:doi: 10.1016/j.ergon.2008.11.003.
   Web of Science ®Google Scholar
• Zhang, H., A. Sekhari, Y. Ouzrout, and A. Bouras. 2016. “Jointly Identifying Opinion Mining Elements and Fuzzy Measurement of Opinion Intensity to Analyze Product Features.” Engineering Applications of Artificial Intelligence 47: 122–139. doi: 10.1016/j.engappai.2015.06.007
   Web of Science ®Google Scholar
• Zhou, F., D. Wu, X. Yang, and J. Jiao. 2008. “‌Ordinal Logistic Regression for Affective Product Design.” 2008 International Conference on Industrial Engineering and Engineering Management, Singapore, 8-11 Dec.
   Google Scholar
• Zhu, Yan, and Gang Chen. 2017. “Research on the Head Form Design of Service Robots Based on Kansei Engineering and BP Neural Network.” Seventh international conference on electronics and information engineering.
   Google Scholar