This paper presents the development and implementation of the Tech4You personal assistant, an AI-driven tool designed to enhance accessibility and engagement within cultural heritage sites, particularly in historically underserved regions like Calabria. Leveraging natural language processing, machine learning, and a robust knowledge base, the assistant provides personalized, multilingual responses, accommodating a diverse spectrum of visitors regardless of language or physical abilities. Authors detail the methodological framework underpinning the assistant's design, including the creation of a comprehensive Knowledge Base, system requirements, and a scalable architecture capable of handling high volumes of interactions. The assistant utilizes advanced technologies such as vector databases and semantic search to accurately interpret and respond to user queries. Preliminary functional tests conducted at sites like Timpone della Motta, Tiriolo, and Mileto demonstrate the assistant's effectiveness in providing accurate and dynamic responses to varied user inquiries. By addressing accessibility challenges and fostering deeper connections to cultural history, it enhances visitor experiences and encourages inquisitive learning.
Leveraging Personal Assistants for Enhanced Access to Cultural Knowledge: A Case Study
Chiurco, Alessandro;D'Augusta, Virginia;Longo, Francesco;Solina, Vittorio;Talarico, Simone
2025-01-01
Abstract
This paper presents the development and implementation of the Tech4You personal assistant, an AI-driven tool designed to enhance accessibility and engagement within cultural heritage sites, particularly in historically underserved regions like Calabria. Leveraging natural language processing, machine learning, and a robust knowledge base, the assistant provides personalized, multilingual responses, accommodating a diverse spectrum of visitors regardless of language or physical abilities. Authors detail the methodological framework underpinning the assistant's design, including the creation of a comprehensive Knowledge Base, system requirements, and a scalable architecture capable of handling high volumes of interactions. The assistant utilizes advanced technologies such as vector databases and semantic search to accurately interpret and respond to user queries. Preliminary functional tests conducted at sites like Timpone della Motta, Tiriolo, and Mileto demonstrate the assistant's effectiveness in providing accurate and dynamic responses to varied user inquiries. By addressing accessibility challenges and fostering deeper connections to cultural history, it enhances visitor experiences and encourages inquisitive learning.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


