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Personalized hotel recommendations based on social networks
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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Title of book
Routledge handbook of hospitality marketingSeries
Routledge HandbooksChapter number
43Pagination
525 - 535Publisher
RoutledgePlace of publication
London, Eng.Publisher DOI
ISBN-13
9781138214668Language
engPublication classification
B1 Book chapterCopyright notice
2017, RoutledgeExtent
49Editor/Contributor(s)
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