Dedicated applications (apps) for child-rearing question and answer (QA) system have become common tools widely used by many parents in Japan. A user can post his/her various questions about child-rearing on the systems and exchange information with other parents online. Since the value of such dedicated applications increases through being used by a large number of users, it is considered important to continuously provide attractive functions to increase user satisfaction. Here, concerns of parents should be changed depending on their children's life stages. In addition, it can be assumed that users always have concerns of child-rearing even when they do not post any questions on the application. Therefore, analysis and comprehension of the problems of parents rearing small children by taking into account these properties will lead to the improving the users' satisfaction of QA services. For instance, the app can provide users with proper information with appropriate timing based on the analysis result. Although topic models are widely known to analyze the content of text data, this is not a sufficient method for visualizing changes in topics over time from question text data, which are relatively short sentences posted on dedicated apps for child-rearing QA systems. In this study, the authors propose an analytical model that can extract the topics of users' concerns from question data and compile topic transitions throughout the various stages of child-rearing. Furthermore, by taking a probabilistic view of the topic transitions, a method for estimating the topic that is most likely to shift from a previous topic at a given time to the next non-question period is constructed. Finally, the authors show the results of applying the proposed method to an actual data set and clarify the usefulness of the estimation result using the proposed method. The proposed method makes it possible to analyze how the worries and concerns of parents raising children evolve over time, and to gain various new insights into the perspectives of support for these users through apps.

In this study, catering robot system, using automate guided vehicle, is developed and introduced to an actual restaurant. Labor productivity of restaurant industry is lowest among service industries. Therefore, labor productivity enhancement is critical mission for the industry. Along with the system introduction, the restaurant staff change their operation; catering process is handover from human staff to AGV. After that, store manager of the restaurant changes weekly work schedule to reduce work hour input. As a result, it is possible to enhance labor productivity by reduction of work hour through the introduction of the system. Also, it is possible to recover robot investment cost by labor cost reduction through the introduction of the system. Further, the system improves employs motivation and teamwork. On the other hands, robot price should be reduced because service site scale is small, collaborative robot should be improved operation speed and safety spec, and multi task robot should be developed because there are many kinds of operation at service site.