dc.contributor.author | Bucciero, Alberto | en_US |
dc.contributor.author | Chirivì, Alessandra | en_US |
dc.contributor.author | Jaziri, Mohamed Ali | en_US |
dc.contributor.author | Muci, Irene | en_US |
dc.contributor.author | Orlandini, Andrea | en_US |
dc.contributor.author | Umbrico, Alessandro | en_US |
dc.contributor.editor | Bucciero, Alberto | en_US |
dc.contributor.editor | Fanini, Bruno | en_US |
dc.contributor.editor | Graf, Holger | en_US |
dc.contributor.editor | Pescarin, Sofia | en_US |
dc.contributor.editor | Rizvic, Selma | en_US |
dc.date.accessioned | 2023-09-02T07:44:22Z | |
dc.date.available | 2023-09-02T07:44:22Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-3-03868-217-2 | |
dc.identifier.issn | 2312-6124 | |
dc.identifier.uri | https://doi.org/10.2312/gch.20231151 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/gch20231151 | |
dc.description.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. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | CCS Concepts: Applied computing → Arts and humanities; Digital libraries and archives; Computing methodologies → Artificial intelligence; Human-centered computing → Interactive systems and tools | |
dc.subject | Applied computing → Arts and humanities | |
dc.subject | Digital libraries and archives | |
dc.subject | Computing methodologies → Artificial intelligence | |
dc.subject | Human | |
dc.subject | centered computing → Interactive systems and tools | |
dc.title | HerMeS - HERitage sMart social mEdia aSsistant: from Requirement Elicitation to Data Modelling for Feeding Artificial Intelligence Recommendation System | en_US |
dc.description.seriesinformation | Eurographics Workshop on Graphics and Cultural Heritage | |
dc.description.sectionheaders | AI and 3D Reconstruction I | |
dc.identifier.doi | 10.2312/gch.20231151 | |
dc.identifier.pages | 1-9 | |
dc.identifier.pages | 9 pages | |