This paper proposes a walking route recommender system aiming at continuously supporting a user to take a walk as means for health promotion. In recent years, taking a walk becomes popular with not only the elderly, but also those from all ages as one of the easiest ways for health promotion. From the viewpoint of health promotion, it is desirable to take a walk as daily exercise. However, walking is very simple activity, which makes it difficult for people to maintain their motivation. Although using an activity monitor is expected to improve the motivation for taking a walk as daily exercise, it forces users to manage their activities by themselves. The proposed system solves such a problem by recommending a walking route that can consume target calories. When a system is to be used for long period of time for supporting user's daily exercise, it should consider the case when a user will not follow the recommended route. It would cause a gap between consumed and target calories. We think this problem becomes serious when a user gradually gets bored with taking a walk during a long period of time. In order to solve the problem, the proposed method implicitly manages calories on monthly basis and recommends walking routes that could keep a user from getting bored. The effectiveness of the recommendation algorithm is evaluated with agent simulation. As another important factor for walking support, this paper also proposes a navigation interface that presents direction to the next visiting point without using a map. As users do not have to continuously focus on the interface, it is not only useful for their safety, but also gives them room to enjoy the landscape. The interface is evaluated by an experiment with test participants.

This paper proposes a visualization system for supporting the task of monitoring bug update information. Recent growth of the Web has brought us various kinds of text stream data, such as bulletin board systems (BBS), blogs, and social networking services (SNS). Bug update information managed by bug tracking systems (BTS) is also a kind of text stream data. As such text stream data continuously generates new data, it is difficult for users to watch it all the time. Therefore, the task of monitoring text stream data inevitably involves breaks of monitoring, which would cause users to lose the context of monitoring. In order to support such a monitoring task involving breaks, the proposed system employs several visualization techniques. The dynamic relationship between bugs is visualized with animation, and a function of highlighting updated bugs as well as that of replaying a part of the last monitoring time is also proposed in order to help a user grasping the context of monitoring. The result of experiment with test participants shows that highlighting and replay functions can reduce frequency of checking data and monitoring time.

This paper proposes a visual analytics (VA) interface for time-series data so that it can solve the problems arising from the property of time-series data: a collision between interaction and animation on the temporal aspect, collision of interaction between the temporal and spatial aspects, and the trade-off of exploration accuracy, efficiency, and scalability between different visualization methods. To solve these problems, this paper proposes a VA interface that can handle temporal and spatial changes uniformly. Trajectories can show temporal changes spatially, of which direct manipulation enables to examine the relationship among objects either at a certain time point or throughout the entire time range. The usefulness of the proposed interface is demonstrated through experiments.