INNOVATION AND CREATIVITY SUPPORT VIA CHANCE DISCOVERY, GENETIC ALGORITHMS, AND DATA MINING

Xavier Llorà (), David E. Goldberg, Yukio Ohsawa, Naohiro Matsumura, Yuichi Washida, Hiroshi Tamura, Masataka Yoshikawa, Michael Welge, Loretta Auvil, Duane Searsmith, Kei Ohnishi and Chen-Ju Chao
Additional contact information
Xavier Llorà: Illinois Genetic Algorithms Lab, University of Illinois at Urbana-Champaign, 117 Transportation Building, 104 S. Mathews Ave., Urbana, IL 61801, USA
David E. Goldberg: Illinois Genetic Algorithms Lab, University of Illinois at Urbana-Champaign, 117 Transportation Building, 104 S. Mathews Ave., Urbana, IL 61801, USA
Yukio Ohsawa: Chance Discovery Consortium, University of Tokyo, Tokyo 112-0012, Japan
Naohiro Matsumura: Graduate School of Economics, Osaka University, Osaka 560-0043, Japan
Yuichi Washida: Research and Development Division, Hakuhodo Inc., Tokyo 108-8088, Japan
Hiroshi Tamura: Research and Development Division, Hakuhodo Inc., Tokyo 108-8088, Japan
Masataka Yoshikawa: Research and Development Division, Hakuhodo Inc., Tokyo 108-8088, Japan
Michael Welge: National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, 1205 W. Clark St., Urbana, IL 61801, USA
Loretta Auvil: National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, 1205 W. Clark St., Urbana, IL 61801, USA
Duane Searsmith: National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, 1205 W. Clark St., Urbana, IL 61801, USA
Kei Ohnishi: Illinois Genetic Algorithms Lab, University of Illinois at Urbana-Champaign, 117 Transportation Building, 104 S. Mathews Ave., Urbana, IL 61801, USA
Chen-Ju Chao: Illinois Genetic Algorithms Lab, University of Illinois at Urbana-Champaign, 117 Transportation Building, 104 S. Mathews Ave., Urbana, IL 61801, USA

New Mathematics and Natural Computation (NMNC), 2006, vol. 02, issue 01, 85-100

Abstract: Creativity protocols and methodologies tend to be time consuming if applied manually. This paper presents how information technologies can support innovation and creativity for collaborative scenario creation and discussion. The fusion of change discovery, genetics algorithms, data mining, and computer-supported collaborative tools provide computational models of innovation and creativity. The proposed technology allows groups of participants in a creative processes to have pervasive access to the analysis of the current scenario in real time. This paper introduces such innovation technologies gathered in the DISCUS project, and summarizes the usage of DISCUS on marketing research workshops.

Keywords: Chance discovery; genetic algorithms; influence diffusion models; computer-mediated communication (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1142/S1793005706000336

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