Bayesian Network を用いた動的アンケートシステムにおける精度向上の取り組み

抄録

User type estimation is an integral problem in providing products and services. One of the most effective ways to estimate user types is to request users to complete a questionnaire. In most cases, a questionnaire has multiple questions and requires considerable user time to complete. To lower the cost of evaluating user type based on a questionnaire, we need to reduce the number of questions in the questionnaire. In our previous study, we proposed an adaptive questionnaire system based on a Bayesian network, which sequentially presents questions according to respondents' answers and then estimates the respondents' user types. To improve the accuracy of respondents' type estimation, we propose two modification methods for this system. One method is the reconstruction of the Bayesian network to reduce the number of questions displayed. The other method is the change of the number of respondents' type estimation. Experimental results show that the latter method is superior to both the former modification method and the original method.