In the last years, several mobile APPs have been developed within the cultural tourism domain to give new impetus to this sector which is booming both in Italy and worldwide. In the wake of the increasing importance of technologies based on artificial intelligence, even mobile applications for the use of cultural tourism heritage are increasingly taking advantage of these techniques. Machine learning strategies are increasingly used to recommend points of interest and itineraries that are compatible with the user's preferences, requirements and constraints. The quality and integrity of the data acquired become the starting point for training and implementing AI models. By levering well-structured data, these algorithms can offer valuable insights, personalised recommendations, and enhanced user interaction in the cultural tourism domain. The HerMeS APP that we present in this paper was designed starting from these premises. The application aims to provide a wide range of artificial intelligence-based features to enhance the enjoyment and exploration of cultural heritage, both tangible and intangible.

HerMeS-HERitage sMart social mEdia aSsistant: from Requirement Elicitation to Data Modelling for Feeding Artificial Intelligence Recommendation System / Bucciero, Alberto; Chirivì, Alessandra; Jaziri Mohamed, Ali; Muci, Irene; Orlandini, Andrea; Umbrico, Alessandro. - In: EUROGRAPHICS TECHNICAL REPORT SERIES. - ISSN 1017-4656. - (2023), pp. 1-9. [10.2312/gch.20231151]

HerMeS-HERitage sMart social mEdia aSsistant: from Requirement Elicitation to Data Modelling for Feeding Artificial Intelligence Recommendation System

Muci Irene
Writing – Review & Editing
;
2023

Abstract

In the last years, several mobile APPs have been developed within the cultural tourism domain to give new impetus to this sector which is booming both in Italy and worldwide. In the wake of the increasing importance of technologies based on artificial intelligence, even mobile applications for the use of cultural tourism heritage are increasingly taking advantage of these techniques. Machine learning strategies are increasingly used to recommend points of interest and itineraries that are compatible with the user's preferences, requirements and constraints. The quality and integrity of the data acquired become the starting point for training and implementing AI models. By levering well-structured data, these algorithms can offer valuable insights, personalised recommendations, and enhanced user interaction in the cultural tourism domain. The HerMeS APP that we present in this paper was designed starting from these premises. The application aims to provide a wide range of artificial intelligence-based features to enhance the enjoyment and exploration of cultural heritage, both tangible and intangible.
2023
applied computing; arts and humanities; digital libraries and archives; computing methodologies; artificial intelligence; human centered computing; interactive systems and tools
01 Pubblicazione su rivista::01a Articolo in rivista
HerMeS-HERitage sMart social mEdia aSsistant: from Requirement Elicitation to Data Modelling for Feeding Artificial Intelligence Recommendation System / Bucciero, Alberto; Chirivì, Alessandra; Jaziri Mohamed, Ali; Muci, Irene; Orlandini, Andrea; Umbrico, Alessandro. - In: EUROGRAPHICS TECHNICAL REPORT SERIES. - ISSN 1017-4656. - (2023), pp. 1-9. [10.2312/gch.20231151]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1718073
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