Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb Experiences

Autoren
V. Arefieva, R. Egger, M. Schrefl, M. Schedl
Paper
Aref22a (2023)
Zitat
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), Singapore, February 27 - March 3, 2023, Demo Paper, ACM Press, pp. 1164–1167 (4 pages), DOI: https://doi.org/10.1145/3539597.3573043, 2023.
Ressourcen
Kopie  (Senden Sie ein Email mit  Aref22a  als Betreff an dke.win@jku.at um diese Kopie zu erhalten)

Kurzfassung (Englisch)

We present Travel Bird, a novel personalized destination recommendation and exploration interface which allows its users to find their next tourist destination by describing their specific preferences in a narrative form. Unlike other solutions, Travel Bird is based on TourBERT, a novel NLP model we developed, specifically tailored to the tourism domain. Travel Bird creates a two-dimensional personalized destination exploration space from TourBERT embeddings of social media content and the users’ textual description of the experience they are looking for. In this demo, we will showcase several use cases for Travel Bird, which are beneficial for consumers and destination management organizations.