Human-Computer Interactive Annealing for Discovering Invisible Dark Events

Experts of chance discovery have recognized a new class of problems where the previous methods fail to visualize a latent structure behind observation. There are invisible events that play an important role in the dynamics of visible events. An invisible leader in a communication network is a typical example. Such an event is named a dark event. A novel technique has been proposed to understand a dark event and to extend the process of chance discovery. This paper presents a new method named “human–computer interactive annealing” for revealing latent structures along with the algorithm for discovering dark events. Demonstration using test data generated from a scale-free network shows that the precision regarding the algorithm ranges from 80% to 90%. An experiment on discovering an invisible leader under an online collective decision-making circumstance is successful.