Related papers: Context-Aware Target Apps Selection and Recommenda…
Diversity-aware data are essential for a robust modeling of human behavior in context. In addition, being the human behavior of interest for numerous applications, data must also be reusable across domain, to ensure diversity of…
People have the ability to make sensible assumptions about other people's emotional states by being sympathetic, and because of our common sense of knowledge and the ability to think visually. Over the years, much research has been done on…
This work presents a novel architecture for context-aware interactions within smart environments, leveraging Large Language Models (LLMs) to enhance user experiences. Our system integrates user location data obtained through UWB tags and…
A novel approach is presented in this work for context-aware connectivity and processing optimization of Internet of things (IoT) networks. Different from the state-of-the-art approaches, the proposed approach simultaneously selects the…
The aim of a clinical decision support tool is to reduce the complexity of clinical decisions. However, when decision support tools are poorly implemented they may actually confuse physicians and complicate clinical care. This paper argues…
The widespread diffusion of connected smart devices has contributed to the rapid expansion and evolution of the Internet at its edge. Personal mobile devices interact with other smart objects in their surroundings, adapting behavior based…
In the era of Web of Things and Services, Context-aware Web Services (CASs) are emerging as an important technology for building innovative context-aware applications. CASs enable the information integration from both the physical and…
Recommender systems, while a powerful decision making tool, are often operationalized as black box models, such that their AI algorithms are not accessible or interpretable by human operators. This in turn can cause confusion and…
This study is motivated by two key considerations: the significant benefits mobile applications offer individuals and businesses, and the limited empirical research on usability challenges. To address this gap, we conducted structured…
In this paper, we discuss one approach for development and deployment of web sites (web pages) devoted to the description of objects (events) with a precisely delineated geographic scope. This article describes the usage of context-aware…
Recommender systems aim to help users find relevant items more quickly by providing personalized recommendations. Explanations in recommender systems help users understand why such recommendations have been generated, which in turn makes…
The proliferation of AI agents, with their complex and context-dependent actions, renders conventional privacy paradigms obsolete. This position paper argues that the current model of privacy management, rooted in a user's unilateral…
Effective recommender systems demand dynamic user understanding, especially in complex, evolving environments. Traditional user profiling often fails to capture the nuanced, temporal contextual factors of user preferences, such as transient…
Many users struggle with effective online search and critical evaluation, especially in high-stakes domains like health, while often overestimating their digital literacy. Thus, in this demo, we present an interactive search companion that…
Many users make quick decisions that affect their data privacy without due consideration of their values. One such decision is whether to download a smartphone app to their device. Previous work has suggested a relationship between values,…
Next-generation augmented reality (AR) promises a high degree of context-awareness - a detailed knowledge of the environmental, user, social and system conditions in which an AR experience takes place. This will facilitate both the closer…
This paper presents e112, a context-aware mobile emergency response application designed to strengthen communication between citizens and authorities during disasters. Building on the ubiquity of smartphones, the system provides SOS…
Multi-agent systems represent a significant advancement in artificial intelligence, enabling complex problem-solving through coordinated specialized agents. However, these systems face fundamental challenges in context management,…
Recommender systems are one of the most successful applications of data mining and machine learning technology in practice. Academic research in the field is historically often based on the matrix completion problem formulation, where for…
When performing visual servoing or object tracking tasks, active sensor planning is essential to keep targets in sight or to relocate them when missing. In particular, when dealing with a known target missing from the sensor's field of…