EDITING AND DISTRIBUTING HUMAN SKILLS WITHIN COMMUNITY VIA FRAGMENTARY ANNOTATIONS ON IMAGE DATA

This paper presents a new approach to develop a know-how distribution support system that aims at facilitating the effective sharing of a variety of technical skills within community, especially focusing on the knowledge exploited to diagnosing image data. By using annotations other expert people attached to the images as clues, the proposed platform supports people to explore prior cases or stored images that are possibly related with current users' interests by providing them with new opportunities of attempting to interpret and/or find meanings of other experts' skills. This platform contributes to the individuals as well as to the community for promoting their awareness about their “selves” and for sharing the skills among members. The proposed platform consists of two networks: the one is constructed based upon the statistical (co-occurrence) relationships involved in the set of annotated data; and the other is extracted from the causal relationships among the annotated data derived by means of the DEMATEL method. These two kinds of relationships do contribute the users in their “storytelling” activity from fragmentary scraps of annotations.