相关论文: Aligning Daily Activities with Personality: Toward…

As recommender systems increasingly guide physical actions, often through wearables and coaching tools, new challenges arise around how users interpret, trust, and respond to this advice. This paper introduces a conceptual framework for…

The quality of sleep has a deep impact on people's physical and mental health. People with insufficient sleep are more likely to report physical and mental distress, activity limitation, anxiety, and pain. Moreover, in the past few years,…

The recent growth of digital interventions for mental well-being prompts a call-to-arms to explore the delivery of personalised recommendations from a user's perspective. In a randomised placebo study with a two-way factorial design, we…

Personality is a psychological factor that reflects people's preferences, which in turn influences their decision-making. We hypothesize that accurate modeling of users' personalities improves recommendation systems' performance. However,…

The recent development of smartphone and wearable sensor technologies enable general public to carry self-tracking tasks more easily. Much work has been devoted to life data collection and visualisation to help people with better…

Mobile proactive tourist recommender systems can support tourists by recommending the best choice depending on different contexts related to herself and the environment. In this paper, we propose to utilize wearable sensors to gather health…

Recent advances in Automated vehicle (AV) technology and micromobility devices promise a transformational change in the future of mobility usage. These advances also pose challenges concerning human-AV interactions. To ensure the smooth…

The rapid spread of digital technologies has produced data-driven feedback loops, wearable devices, social media networks, and mobile applications that shape user behavior, motivation, and mental well-being. While these systems encourage…

Traditional recommender systems primarily rely on a single type of user-item interaction, such as item purchases or ratings, to predict user preferences. However, in real-world scenarios, users engage in a variety of behaviors, such as…

Recommender system has been deployed in a large amount of real-world applications, profoundly influencing people's daily life and production.Traditional recommender models mostly collect as comprehensive as possible user behaviors for…

Sleep is critical to leading a healthy lifestyle. Each day, most people go to sleep without any idea about how their night's rest is going to be. For an activity that humans spend around a third of their life doing, there is a surprising…

Promoting healthy lifestyle behaviors remains a major public health concern, particularly due to their crucial role in preventing chronic conditions such as cancer, heart disease, and type 2 diabetes. Mobile health applications present a…

We propose a model of the situational context of a person and show how it can be used to organize and, consequently, reason about massive streams of sensor data and annotations, as they can be collected from mobile devices, e.g.…

Artificial Intelligence is being employed by humans to collaboratively solve complicated tasks for search and rescue, manufacturing, etc. Efficient teamwork can be achieved by understanding user preferences and recommending different…

Subjective well-being is a cornerstone of individual and societal health, yet its scientific measurement has traditionally relied on self-report methods prone to recall bias and high participant burden. This has left a gap in our…

We propose and create an incentive based recommendation algorithm aimed at improving the lifestyle of diabetic patients. This algorithm is integrated into a real world mobile application to provide personalized health recommendations.…

Mobile applications and on-body devices are becoming increasingly ubiquitous tools for physical activity tracking. We propose utilizing a self-tracker's habits to support continuous prediction of whether they will reach their daily step…

Users can easily export personal data from devices (e.g., weather station and fitness tracker) and services (e.g., screentime tracker and commits on GitHub) they use but struggle to gain valuable insights. To tackle this problem, we present…

Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to transportation, energy utilization, and resource consumption…

Modern society devotes a significant amount of time to digital interaction. Many of our daily actions are carried out through digital means. This has led to the emergence of numerous Artificial Intelligence tools that assist us in various…