Effectively-Heterogeneous Information Extraction To Stimulate
Divergent Thinking
Conflicts in different concepts are often useful in creating new ideas. We
have proposed an outsider model in which an artificial agent provides
``effectively-heterogeneous'' information to support human divergent-oriented
discussions. Subjective experiments using a prototype system based on the
outsider model and a detailed analysis on results confirming that the
outsider model can extract information containing hidden relevance, i.e.,
``effective-heterogeneousness'', are presented.