[KAIST News] Prof. Juyong PARK, appointed guest editor of the Palgrave Communication
[JoongAng SUNDAY] Chuseok 3 pm, son and daughter-in-law turn into son-in-law and daughter | Prof. Wonjae LEE
[Electronic Times] Developed a technology to reduce "Character Rigging" workload with algorithm | Prof. Sung-Hee LEE
[THIS IS GAME] "The most necessary game for Korea" | Prof. Young Yim DOH
Selected in the DaVinci Idea Competition 2018 | Joo Young OH (PhD student)
Excellent Presentation Paper Award at the KCC2018 | Jee Jung CHOI (PhD student)
SIGGRAPH 2018 ACM Student Research Competition - First Place | Seungbae BANG
[Electronic Times] KAIST, AI learning based music recommendation technology developed | Prof. Juhan NAM
[Dong-A Ilbo] AI Pianist... Only ‘reckless research’ is sponsored | Prof. Juhan NAM
[Yonhap News] New board member of KCTI | Prof. Young Yim DOH
[KAIST 2017 Annual R&D Report] Prof. Ji-Hyun LEE
Published: KAIST 2017 Annual R&D Report

A Study for Metadata Structure and Recommender of Biological Systems to Support a Bio-inspired Design
Graduate School of Culture Technology | Ji-Hyun Lee · Sun-Joong Kim

Bio-inspired design is the design method encouraging breakthrough innovations by stimulating analogical reasoning of designers. However, most of the time, designers choose wrong metaphors to do the bio-inspired design. As long as they are novice in natural science, this problem cannot be solved. To resolve this problem, the recommendation system has been developed and evaluated. Specifically, the representation framework that stores biological characteristics of BSs at the holistic perspective of ‘physical, biological, and ecological relations’ is redesigned and the retrieval system that is operated on the representation framework is implemented for designers. The representation framework was complemented by the systematic indexing mechanisms and the causal model based ontology. This research could dramatically increase the solution space of designers and guide the designers to choose appropriate metaphor from the nature.

Original: https://ct.kaist.ac.kr/upload/files/20180525-KAIST2017R&D-Eng.pdf