In recent years, networking has spread substantially owing to the rapid developments made in Information & Communication Technology (ICT). It has also become easy to share highly contextual data and information, including ideas, among people. On the other hand, there exists information that cannot be expressed in words (tacit knowledge) and useful knowledge or know-how that is not shared well in an organization. The idea generation method enables the expression of explicit knowledge, which enables the expression of tacit knowledge by words, and can utilize explicit knowledge as know-how in organizations. We propose an idea generation consistent support system, GUNGEN-Web II. This system has suggestion functions for a concrete idea label and a concrete island name. The suggestion functions convey an idea and the island name to other participants more precisely. This system also has an illustration support function and a document support function. In this study, we aimed to improve the quality of the sentence obtained using the KJ method. We compared the results of our proposed systems with conventional GUNGEN-Web by conducting experiments. The results are as follows: The evaluation of the sentence of GUNGEN-Web II was significantly different to those obtained using the conventional GUNGEN-Web.

Recent idea visualization programs still lack automatic idea summarization capabilities. This paper presents a knowledge-based method for automatically providing a short piece of English text about a topic to each idea group in idea charts. This automatic topic identification makes used Yet Another General Ontology (YAGO) and Wordnet as its knowledge bases. We propose a novel topic selection method and we compared its performance with three existing methods using two experimental datasets constructed using two idea visualization programs, i.e., the KJ Method (Kawakita Jiro Method) and mind-mapping programs. Our proposed topic identification method outperformed the baseline method in terms of both performance and consistency.

Practitioners of the Jiro Kawakita (KJ) method, a method for organizing ideas, typically use paper labels and four-colored ball-point pens to record their ideas during the creative thinking process. A similar approach is used in group KJ method sessions; however, the effectiveness of capturing and sharing the diagrams and information is limited because of the large amount of paper required. Considering the merits of the conventional paper-pen approach and the demand for quick sharing of diagrams after a session, we designed and implemented a system to digitize group KJ sessions--not just the diagrams but also the details of the creative process. We used digital pens during the session to capture the position and orientation of labels as well as their content. We confirmed the efficiency of our system by applying it to several GKJ sessions.

The groupware for new idea generation system, GUNGEN, has been developed. GUNGEN consists of a distributed and cooperative KJ method support system and an intelligent productive work card support system. The system was implemented on a network consisting of a number of personal computers. The distributed and cooperative KJ method is carried out on computers. The ideas proposed by participants are classified into several groups on the basis of similarity and then a conclusion is derived. The intelligent productive work card support system can be used as a multimedia database to refer to the previous data of the distributed and cooperative KJ method.