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Contextual information is vital for accurate trajectory prediction. For instance, the intricate flying behavior of migratory birds hinges on their analysis of environmental cues such as wind direction and air pressure. However, the diverse…
Finding the next venue to be visited by a user in a specific city is an interesting, but challenging, problem. Different techniques have been proposed, combining collaborative, content, social, and geographical signals; however it is not…
As social service robots become commonplace, it is essential for them to effectively interpret human signals, such as verbal, gesture, and eye gaze, when people need to focus on their primary tasks to minimize interruptions and…
Being able to automatically and quickly understand the user context during a session is a main issue for recommender systems. As a first step toward achieving that goal, we propose a model that observes in real time the diversity brought by…
Designing Conversational AI systems to support older adults requires these systems to explain their behavior in ways that align with older adults' preferences and context. While prior work has emphasized the importance of AI explainability…
Any organization needs to improve their products, services, and processes. In this context, engaging with customers and understanding their journey is essential. Organizations have leveraged various techniques and technologies to support…
Conversational recommender systems offer the promise of interactive, engaging ways for users to find items they enjoy. We seek to improve conversational recommendation via three dimensions: 1) We aim to mimic a common mode of human…
Prompting is central to interaction with AI systems, yet many users struggle to explore alternative directions, articulate creative intent, or understand how variations in prompts shape model outputs. We introduce prompt recommender systems…
Robots operating in human-shared environments must not only achieve task-level navigation objectives such as safety and efficiency, but also adapt their behavior to human preferences. However, as human preferences are typically expressed in…
Robots are increasingly entering the daily lives of families, yet their successful integration into domestic life remains a challenge. We explore family routines as a critical entry point for understanding how robots might find a…
Various studies have been conducted on human-supporting robot systems. These systems have been put to practical use over the years and are now seen in our daily lives. In particular, robots communicating smoothly with people are expected to…
To hold a true conversation, an intelligent agent should be able to occasionally take initiative and recommend the next natural conversation topic. This is a challenging task. A topic suggested by the agent should be relevant to the person,…
Modern Security Operations Centres (SOCs) integrate diverse tools, such as SIEM, IDS, and XDR systems, offering rich contextual data, including alert enrichments, flow features, and similar case histories. Yet, analysts must still manually…
In this work we address the development of a smart personal assistant that is capable of anticipating a user's information needs based on a novel type of context: the person's activity inferred from her check-in records on a location-based…
Context as the dynamic information describing the situation of items and users and affecting the users decision process is essential to be used by recommender systems in mobile commerce to guarantee the quality of recommendation. This paper…
The rising influence of social media platforms in various domains, including tourism, has highlighted the growing need for efficient and automated Natural Language Processing (NLP) strategies to take advantage of this valuable resource.…
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…
Virtual reality allows creating highly immersive visual and auditory experiences, making users feel physically present in the environment. This makes it an ideal platform to simulate dangerous scenarios, including fire evacuation, and study…
In human-robot interaction, robots must communicate in a natural and transparent manner to foster trust, which requires adapting their communication to the context. In this paper, we propose using Petri nets (PNs) to model contextual…
In this paper, we develop an embodied AI system for human-in-the-loop navigation with a wheeled mobile robot. We propose a direct yet effective method of monitoring the robot's current plan to detect changes in the environment that impact…