  More than 80 civic tech communities in Japan are developing information
technology (IT) systems to solve their regional issues. Collaboration among
such communities across different regions assists in solving their problems
because some groups have limited IT knowledge and experience for this purpose.
Our objective is to realize a civic tech matchmaking system to assist such
communities in finding better partners with IT experience in their issues. In
this study, as the first step toward collaboration, we acquire relevant social
issues and information technologies by association rule mining. To meet our
challenge, we supply a questionnaire to members of civic tech communities and
obtain answers on their faced issues and their available technologies.
Subsequently, we match the relevant issues and technologies from the answers.
However, most of the issues and technologies in this questionnaire data are
infrequent, and there is a significant bias in their occurrence. Here, it is
difficult to extract truly relevant issues--technologies combinations with
existing interestingness measures. Therefore, we introduce a new measure called
weighted casual confidence, and show that our measure is effective for mining
relevant issues--technologies pairs.
