Personalized Hotel Recommendation based on Social Networks

نویسندگان

  • Shaowu Liu
  • Gang Li
چکیده

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 start to seek recommendations and advises from websites like TripAdvisor and Yelp. While travelers are willing to share their opinions on social networks, this provides an opportunity for hospitality businesses to learn their customers’ preferences. Given these preferences data, recent advances in machine learning research has made it possible to build automatic recommender systems that can generate hotel recommendations tailored for each traveler. This chapter introduces the basic concepts and tools for creating hotel recommender systems.

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تاریخ انتشار 2016