Traditional recommender systems suggest Cultural and Natural Heritage items to visitors by matching the target user to the available options, one-to-one. However, the increasing diffusion of informal activities and events, supported by location-based services such as Airbnb, extends personalized recommendation to a many-to-one match-making task. Airbnb experiences, which any citizen can propose to offer geographic tours and thematic activities, are composed of at least two entities to be evaluated: the former is the experience itself (in terms of topic, cost, etc.); the latter is the host, who directly interacts with guests during the management of the planned activities. As both entities can dramatically influence guests' perceptions, they should be jointly taken into account by recommender systems. This paper presents our preliminary work aimed at extending the personalized suggestion of Cultural Heritage items to such composite objects.

Beyond Traditional Cultural Heritage Recommender Systems: Suggesting Airbnb Experiences to Users

Noemi Mauro;Liliana Ardissono;Giovanna Petrone;Angelo Geninatti Cossatin;Claudio Mattutino
2021-01-01

Abstract

Traditional recommender systems suggest Cultural and Natural Heritage items to visitors by matching the target user to the available options, one-to-one. However, the increasing diffusion of informal activities and events, supported by location-based services such as Airbnb, extends personalized recommendation to a many-to-one match-making task. Airbnb experiences, which any citizen can propose to offer geographic tours and thematic activities, are composed of at least two entities to be evaluated: the former is the experience itself (in terms of topic, cost, etc.); the latter is the host, who directly interacts with guests during the management of the planned activities. As both entities can dramatically influence guests' perceptions, they should be jointly taken into account by recommender systems. This paper presents our preliminary work aimed at extending the personalized suggestion of Cultural Heritage items to such composite objects.
2021
Workshop on Personalized Access to Cultural Heritage
Utrecht, The Netherlands
21-25 June 2021
Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
ACM
203
207
978-1-4503-8367-7
https://dl.acm.org/doi/proceedings/10.1145/3450614?tocHeading=heading5
review-based recommender systems, experience modeling, Cultural Heritage
Noemi Mauro, Liliana Ardissono, Giovanna Petrone, Angelo Geninatti Cossatin, Claudio Mattutino
File in questo prodotto:
File Dimensione Formato  
PATCH_2021.pdf

Accesso aperto

Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 434.06 kB
Formato Adobe PDF
434.06 kB Adobe PDF Visualizza/Apri
editorialVersion.pdf

Accesso riservato

Descrizione: Articolo completo
Tipo di file: PDF EDITORIALE
Dimensione 536.01 kB
Formato Adobe PDF
536.01 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1788277
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact