Personalized Hotel Recommendation based on Social Networks

Publisher:
Routledge
Publication Type:
Chapter
Citation:
Routledge Handbook of Hospitality Marketing, 2018
Issue Date:
2018
Metrics:
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Recommender systems have become an important tool for users to identify interesting items as well as for businesses to promote their products to the right users. With the rapid development of social networks, travelers have started to seek recommendations and advice from web services such as TripAdvisor and Yelp. Although the initial purpose of travelers is to share their opinions on social networks, this provides an opportunity for hospitality businesses to learn about their customers’ preferences. Given these data on preferences, recent advances in data science research have made it possible to build automatic recommender systems that can generate hotel recommendations tailored to each traveler. This chapter introduces the basic concepts and tools for creating hotel recommender systems
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