Associated with the Linz Institute of Technology and the Institute of Computational Perception @ JKU Linz, Austria

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

Demo_WSDM_2023 Teaser

Abstract

Personalized recommendation systems for tourism have received more attention in recent years since society has entered the era of experience-based economy that changes both traveler and destination management behavior. User-generated data such as social media posts, online reviews, and others, provide a solid basis for tourism business solutions like platforms for personalized recommendations and public opinion monitoring which are built using natural language processing techniques. However, the majority of destination recommender systems are built with a user's search history or interaction data using collaborative or content-based filtering In contrast, 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 both consumers and destination management organizations.


Citation

Veronika Arefieva, Roman Egger, Michael Schrefl, Markus Schedl
Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb Experiences
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), 2023.

BibTeX

@inproceedings{Arefieva2023Demo_WSDM_2023,
    title = {Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb Experiences},
    author = {Arefieva, Veronika and Egger, Roman and Schrefl, Michael and Schedl, Markus},
    booktitle = {Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023)},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    location = {Singapore, Singapore},
    month = {February-March},
    year = {2023}
}

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