Development of Association Recommend Function for a Cross-curricular Subject Education Database as an Example in Disaster Prevention Education

Abstract

This study would like to suggest an association recommend function as a framework to compensate for the shortcomings of the search type method, by incorporating a recommend type information collection into the database, in order to effectively support teachers working on disaster prevention education. The similarity scores of individual contents in an item base were calculated, and a plug-in which displays the association mapping based on the calculation was developed. As a result of operation verification, the achieved recommend information targeted by the purposed association recommends function could be visually displayed.