Computational methods for discoveries from integrated data - Human-interactive annealing for multilateral observation

Abstract

Unobserved events play an important role in the dynamics of observed events. They are either something hidden intentionally, or something new not yet recognized. Such invisible events are named dark events. A new method named human-interactive annealing is presented to understand the threat arising from the dark events and to invent a scenario to turn the threat to opportunity. The method is extended for integrated data from multilateral observation. A scenario invention experiment is demonstrated using patent documents in the field of knowledge acquisition to design corporate R&D strategies. Multilateral observation provides more clues when the engineers and strategists obtain an idea on emerging technologies. © 2008 Springer-Verlag Berlin Heidelberg.