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Personalized hotel recommendations based on social networks

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posted on 2017-01-01, 00:00 authored by Shaowu Liu, Gang LiGang Li
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.

History

Title of book

Routledge handbook of hospitality marketing

Series

Routledge Handbooks

Chapter number

43

Pagination

525 - 535

Publisher

Routledge

Place of publication

London, Eng.

ISBN-13

9781138214668

Language

eng

Publication classification

B1 Book chapter

Copyright notice

2017, Routledge

Extent

49

Editor/Contributor(s)

D Gursoy

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