%0 Conference Paper %1 Occhioni_2023 %A Occhioni, Daria %A Ferrato, Alessio %A Limongelli, Carla %A Mezzini, Mauro %A Sansonetti, Giuseppe %A Micarelli, Alessandro %B Workshop on Personalized Access to Cultural Heritage at the 31st ACM Conference on User Modeling, Adaptation and Personalization %D 2023 %I ACM %K art-recommender eye-tracking umap2023 %P 374-378 %R 10.1145/3563359.3596670 %T Eyeing the Visitor's Gaze for Artwork Recommendation %U https://doi.org/10.1145%2F3563359.3596670 %X Recommender systems (RSs) are increasingly present in our everyday lives for business and pleasure. The Cultural Heritage domain is no exception. In the research literature, several RSs have been proposed to enhance the fruition of artistic and cultural resources. In this paper, we present some of our research activities aimed at realizing a RS for suggesting personalized itineraries to exhibit and museum visitors. More specifically, we describe the collection and use of eye-tracking data to understand if there are any correlations between the visitors’ gaze patterns and their degree of appreciation of the viewed artworks. If such correlations exist, they could be used as implicit feedback in the recommendation engine. The preliminary results are interesting and encourage us to pursue our research activities.

@inproceedings{Occhioni_2023, abstract = {Recommender systems (RSs) are increasingly present in our everyday lives for business and pleasure. The Cultural Heritage domain is no exception. In the research literature, several RSs have been proposed to enhance the fruition of artistic and cultural resources. In this paper, we present some of our research activities aimed at realizing a RS for suggesting personalized itineraries to exhibit and museum visitors. More specifically, we describe the collection and use of eye-tracking data to understand if there are any correlations between the visitors’ gaze patterns and their degree of appreciation of the viewed artworks. If such correlations exist, they could be used as implicit feedback in the recommendation engine. The preliminary results are interesting and encourage us to pursue our research activities.}, added-at = {2023-06-28T16:02:50.000+0200}, author = {Occhioni, Daria and Ferrato, Alessio and Limongelli, Carla and Mezzini, Mauro and Sansonetti, Giuseppe and Micarelli, Alessandro}, biburl = {https://www.bibsonomy.org/bibtex/2e65f20c81dc0b803a232f978910d5825/brusilovsky}, booktitle = {Workshop on Personalized Access to Cultural Heritage at the 31st {ACM} Conference on User Modeling, Adaptation and Personalization}, description = {Eyeing the Visitor’s Gaze for Artwork Recommendation | Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization}, doi = {10.1145/3563359.3596670}, interhash = {a16a734da683443f9cd8edaa64618e6e}, intrahash = {e65f20c81dc0b803a232f978910d5825}, keywords = {art-recommender eye-tracking umap2023}, month = jun, pages = {374-378}, publisher = {{ACM}}, timestamp = {2023-06-28T16:02:50.000+0200}, title = {Eyeing the Visitor's Gaze for Artwork Recommendation}, url = {https://doi.org/10.1145%2F3563359.3596670}, year = 2023 }