Innovation and Creativity Support via Chance Discovery, Genetic Algorithms, and Data Mining

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.

Graph-theoretic measure for active iGAs

“…In order to compute such a measure the authors need two components: i) cycle detection capabilities for a given graph G at time t (G t ), and ii) an heuristic to quantify how much inconsistency the detected cycle is introducing. A detailed explanation of this property can be found elsewhere [15].…”

“…Thus, due to the greater than relations (contained in E ), the consistency of the user evaluations can be identified. This property is the basis of the consistency metric [15]. In order to compute such a measure the authors need two components: i) cycle detection capabilities for a given graph G at time t (G t ), and ii) an heuristic to quantify how much inconsistency the detected cycle is introducing.…”

Speeding online synthesis via enforced selecto-recombination

“…However, genetic algorithms have also entered areas ruled by aesthetic criteria; interactive genetic algorithms [18] are a clear exponent of collaborative human-computer problem solving where no objective, but subjective, function can be defined. Moreover, social aspects of genetic algorithms have shown how they can act as models of human innovation and creativity [12,8,13,20]-as postulated by Goldberg [5]. Human-based genetic algorithms (HBGAs) target human process by drawing from the lessons learned from their computational counterparts.…”

“…Human-based genetic algorithms can be metaphors of organizations, but also models of human innovation and creativity. Early efforts have shown the benefits of modeling creative processes after the evolutionary metaphor [8,13]. However, those efforts lacked of quantitative analysis.…”

VAST to Knowledge: Combining tools for exploration and mining

“…DISCUS: DISCUS 3 encompasses several analytics tools. Summarizer is used to rank the sentences and words of a collection and collection subsets [3]. The ranking is based on a mutually reinforcing relationship between sentences and terms: important sentences include many important terms, and conversely, important terms are included by many important sentences.…”