Beyond Traditional Cultural Heritage Recommender Systems: Suggesting Airbnb Experiences to Users
| Autor: | Angelo Geninatti Cossatin, Liliana Ardissono, Giovanna Petrone, Claudio Mattutino, Noemi Mauro |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Matching (statistics)
Computer science media_common.quotation_subject 02 engineering and technology review-based recommender systems Cultural Heritage Recommender system Task (project management) Cultural heritage World Wide Web review-based recommender systems experience modeling Cultural Heritage 020204 information systems Perception Natural heritage 0202 electrical engineering electronic engineering information engineering experience modeling 020201 artificial intelligence & image processing Host (network) media_common |
| Zdroj: | UMAP (Adjunct Publication) |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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