Kenichi Horie

Human-Interactive Annealing Process with Pictogram for Extracting New Scenarios for Patent Technology

The latent structure behind an observation often plays an important role in the dynamics of visible events. Such latent structure is composed of invisible events named dark events. Human-interactive annealing is developed to visualize and understand dark events. This paper presents an application of human-interactive annealing for extracting new scenarios for patent technology using the latent technology structure behind current patented technology.

Human-interactive annealing for turning threat to opportunity in technology development

Human-interactive annealing is a new method for understanding invisible but relevant events, and inventing hypothetical scenarios. The human-interactive annealing is elaborated for texts. It is applied to patents for acquiring opportunity in technology development. An illustrative experiment on discovering opportunity by analyzing US patent texts on knowledge acquisition is demonstrated. A few sample hypothetical scenarios on emerging technological elements are obtained

Extracting high quality scenario for consensus on specifications of new products

In this study, analysis has been executed on the scenarios for consensus on specifications of new products, which were extracted with the refinement of Double Helix Loop process for Chance Discovery. The aim of this analysis was to confirm that SCENARIO MAP, which refines KeyGraph by attaching macro photography of defects on the undefined names of the defects on its nodes, helps examinees to extract high quality scenarios through group discussion and to find the roles of SCENARIO MAP and Group discussion with its effect. 11 high quality scenarios for future proposal were extracted successfully after 104 scenarios. We found that SCENARIO MAP played the role to help examinees to identify the undefined defects and interpret the context of objective data and subjective data easily and the group discussion accelerated them to exchange their inherent experiences, know how and knowledge. The human centric process of SCENARIO MAP and group discussion can be regarded to give effect to extract these high quality scenarios.

Emerging novel scenarios of new product design with teamwork on scenario maps using pictorial keygraph

We developed a method of teamwork for products design in real manufacturing company, where Scenario Maps using Pictorial KeyGraph assist creating novel scenarios of new product design. In Pictorial KeyGraph, photographs of physical objects corresponding to incomprehensible items in given data are embedded to the visual result of KeyGraph applied to their business report. In their communications with Pictorial KeyGraph, novel and practical scenarios of new products design were extracted, and 5 new patents have been applied. We found evidences that the team members tend to combine established concepts via rare words in creative designing.

Designing New Product Scenarios for Patent by Human-Interactive Annealing with Pictogram

Latent structure behind observation often plays an important role in the dynamics of visible events. Such latent structure is composed of invisible events named dark event. Human-interactive annealing is developed to visualize and understand dark events. This paper presents application of the human-interactive annealing with pictogram for designing new product scenarios for patent from latent technology structure behind current patented technology. Pictogram aided examinees not only to reinterpret the event map more precisely and deeply but also to create six new scenarios for patent. Two of them are novel scenarios and worthy of consideration for new patent application

Condensation and Picture Annotations of Scenario Map for Consensus in Scenario Mining

In this paper, we propose a method for supporting the emergence of admissible scenario from KeyGraph with the “condensed” visualized relations of concepts. We can count sub methods addressed in this study. First, based on a simplified ontology-based framework, we made a method for refining the structure of KeyGraph from a initial graph obtained for discursive writings. For realizing a further restructuring of KeyGraph, we also developed a technique for recomposing morphemes by applying rules of phrase compositions. Second, the hierarchical context classification enabled to focus the data for the user’s interest. Third, by attaching scenic information i.e. pictures, to the refined KeyGraph, we realized admissible scenarios of earthquake signs. Here three participants of scenario creation meeting evaluated the admissibility on achieving consensus.

Computational Methods for Discoveries from Integrated Data-Human-Interactive Annealing for Multilateral Observation

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.