Billions of live-streaming viewers share their opinions on scenes they are watching in real-time and interact with the event, commentators as well as other viewers via text comments. Thus, there is necessary to explore viewers’ comments with scenes in E-sport live-streaming events. In this paper, we developed CS-lol, a new large-scale dataset containing comments from viewers paired with descriptions of game scenes in E-sports live-streaming. Moreover, we propose a task, namely viewer comment retrieval, to retrieve the viewer comments for the scene of the live-streaming event. Results on a series of baseline retrieval methods derived from typical IR evaluation methods show our task as a challenging task. Finally, we release CS-lol and baseline implementation to the research community as a resource.

Recommendation algorithms automatically suggest news articles based on past behavioral logs. There has been reported cases of mental health problems caused by continuous consumption of negative articles, besides recommendation algorithms has a problem of over-recommendation which may induce continuous consumption of negative articles. Although research on the relationship between negative news article consumption and mental health has been conducted via small-scale user interviews, large-scale behavioral research on user engagement with recommended news articles has not been carried out. Therefore, we comprehensively investigated how the emotional polarity of articles affects each indicator of user attention by assigning emotional labels to news articles using crowdsourcing and analyzing about 1 million user behavior logs that viewed these articles. To the best of our knowledge, this is one of the first publicly available studies to analyze the impact of negative articles on users' news consumption behavior on an online news platform. The findings indicated that negative articles, irrespective of their category, were more likely to be clicked on, were read for longer durations, and had lower bounce rates. Furthermore, users showed greater interest in negative news related to entertainment and sports. These findings can be used as a first step for news platforms to build safer recommendation algorithms that consider the psychological impact on users.

Practical news feed platforms generate a hybrid list of news articles and advertising items (e.g., products, services, or information) and many platforms optimize the position of news articles and advertisements independently. However, they should be arranged with careful consideration of each other, as we show in this study, since user behaviors toward advertisements are significantly affected by the news articles. This paper investigates the effect of news articles on users' ad consumption and shows the dependency between news and ad effectiveness. We conducted a service log analysis and showed that sessions with high-quality news article exposure had more ad consumption than those with low-quality news article exposure. Based on this result, we hypothesized that exposure to high-quality articles will lead to a high ad consumption rate. Thus, we conducted million-scale A/B testing to investigate the effect of high-quality articles on ad consumption, in which we prioritized high-quality articles in the ranking for the treatment group. The A/B test showed that the treatment group's ad consumption, such as the number of clicks, conversions, and sales, increased significantly while the number of article clicks decreased. We also found that users who prefer a social or economic topic had more ad consumption by stratified analysis. These insights regarding news articles and advertisements will help optimize news and ad effectiveness in rankings considering their mutual influence.

Personalization plays an important role in many services. To evaluate personalized rankings, online evaluation, such as A/B testing, is widely used today. Recently, multileaving has been found to be an efficient method for evaluating rankings in information retrieval fields. This paper describes the first attempt to optimize the multileaving method for personalization settings. We clarify the challenges of applying this method to personalized rankings. Then, to solve these challenges, we propose greedy optimized multileaving (GOM) with a new credit feedback function. The empirical results showed that GOM was stable for increasing ranking lengths and the number of rankers. We implemented GOM on our actual news recommender systems, and compared its online performance. The results showed that GOM evaluated the personalized rankings precisely, with significantly smaller sample sizes (< 1/10) than A/B testing.

In this study, we aim at realizing autonomous simultaneous flight of multiple small helicopters. In such situation, collision avoidance of the helicopters should be considered in guidance control system to improve safety and reliability of the flight system. In this paper, we construct a collision-free guidance control system for multiple small helicopters. The collision avoidance problem is regarded as a control problem with state restrictions, and the theory of Nonlinear Model Predictive Control (NMPC) is applied to the guidance control system. A simple nonlinear guidance model is used for design of NMPC to reduce the computational cost. A novel position constraint is proposed for optimizing the avoidance trajectory of each helicopter. The effectiveness of the designed control system and proposed constraints are verified by numerical simulation and flight experiment.

Lunar rovers are required to move on rough terrains such as in craters and rear cliffs where it is scientifically very important to explore. Recently, wheel typed rovers are popular for planetary exploration missions. However, there is a problem that the wheel typed rovers have possibility of stack. Therefore, this paper investigates a mechanism of kinetic behavior between the wheels of the exploration rovers and soil. The important parameters are extracted by considering the mechanism. This paper proposes an elastic wheel by considering the important parameters. The elastic wheel has the surface which can be changed flexibly toward rough terrain. Running experiments on soil which imitated regolith are carried out to observe the traversability of the elastic wheel using slip ratio and sinkage.

In future planetary exploration missions, robots are required to traverse over very rough terrain. On the surface of the moon there are covered with soils, which is named regolith. Regolith is easy to slide. Any stack may occur to the robots that are running on the regolith. Some researchers have studied the mobility system for robots. However the optimal and robust mobility systems have not been developed yet. For producing high traversability, this paper proposes a new wheel system, considering the characteristic of soil made a new wheel

Planetary exploration robots are required to explore rough and steep areas such as craters and cliffs to achieve scientific goals. Most of the proposed rovers have some wheels to move on a planetary surface. However, it is difficult to traverse on a rough terrain flexibly. A legged rover can provide higher capability of moving in such a rough terrain than wheeled robots. Therefore the authors have studied a small and lightweight rover which can move across a rough terrain such as a steep slope inside craters. This paper deals with design scheme for a light walking rover for planetary exploration. This paper presents analysis on the proposed weight arrangement scheme to reduce the weight of the walking robots. The effectiveness of the proposed scheme is shown by computer simulation and hardware study.

Performance of mobility is highly dependent on the gravitational environment. Some researchers have proposed novel locomotion methods for extremely small terrestrial bodies like asteroids. Hopping is a possible method under micro-gravity. It is not proved, however, that the proposed method of locomotion is optimum for a given level of gravity. The purpose of this paper is to analyze which level of gravity is optimum for each mechanism, and which mechanism or parameter is optimum for each level of gravity. First, a classification of locomotion mechanism is described. Next, the speed of hopping and wheeled robots is compared. Finally, some simulation studies are performed to analyze the detailed mobility of wheeled robots.