ARTU: An Approach for Recommending Trips to Users
Mario Casillo, Francesco Colace, Marco Lombardi, Angelo Lorusso, Domenico Santaniello, Carmine Valentino · IEEE Access · 2025
Context-Aware Computing encompasses methods and technologies designed to interpret environmental data and react accordingly, to reduce and streamline interactions between users and digital systems. In this context, Context Awareness (CA) can be viewed as a set of technological capabilities that enrich service delivery across multiple application domains. In recent years, e-Tourism and Cultural Heritage fields have emerged as prominent areas for such research. Advances in technology now allow travelers to access tailored content and services throughout all stages of their journey, each phase presenting distinct needs and objectives. This evolution underscores the growing importance of Recommendation Systems, which aim to suggest relevant content or services by factoring in user preferences and contextual factors. This study investigates Context-Aware Recommender Systems (CARS), focusing on how contextual dimensions can be effectively modeled and integrated within a specific application setting. In this framework, a system architecture was designed to deliver e-Tourism content and services in a way that meaningfully promotes Cultural Heritage, adapting dynamically to both contextual conditions and user profiles. The innovative aspect of this approach lies in its treatment of information delivery to the end-user, which is framed through three foundational lenses: Knowledge Management, Contextual Awareness, and Recommender Systems. A prototype application, named ARTU, was developed according to this architecture, aiming to assist users in crafting personalized, context-aware itineraries linked to key cultural landmarks in the Campania region of Southern Italy. Experimental results affirm the system’s operational effectiveness and adaptability.