Abstract
In regards to information technology of modern society, IT convergence technology is applied in various fields. Particularly, active studies are conducted for creative design products with the use of IT convergence technology in design industry which transforms sensibility of people into various expressions. People started to put high significance to design elements and sensibility accordingly with diverse and distinctive lifestyle and active studies are also conducted on sensibility engineering interaction method which connects sensibility of people with design to satisfy such demand. Also, since distributed processing became available, advancement from server centered information processing and network, such strength is applied to design industry as well. The purpose of this study lies in recommending and proposing P2P context awareness based sensibility design using color and bio-signal analysis. In order to express design that coincides with distinctive and differentiated sensibility of people, the proposed method analyzes relation between visual sensibility and color design with the use of statistic analysis tool R 3.1.0 and SPSS 21.0 and the clustering of users with similar sensibility is conducted with the use of P2P network based context awareness. It recommends color design that coincides with the sensibility of new user by using the P2P network based collaborative filtering and applying it to color design based on clustered users. Proposed method reduces the time and cost spent to estimate design that satisfies the sensibility and requirement of user and supports companies to have concrete and clarified grasp on ambiguous personal requirement of user.
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Notes
The R project, www.r-project.org
SPSS, www.spss.co.kr
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Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A1A2059964).
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Jung, H., Chung, K. P2P context awareness based sensibility design recommendation using color and bio-signal analysis. Peer-to-Peer Netw. Appl. 9, 546–557 (2016). https://doi.org/10.1007/s12083-015-0398-z
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DOI: https://doi.org/10.1007/s12083-015-0398-z