Abstract
Today the internet is flooded with lots of e-commerce applications and social networking sites. Many websites and mobile applications have been developed to provide services to different kinds of users, and tourism is one of these sectors. People enjoy sharing their experiences and learning from others' experiences. Here, the recommender system comes into the picture for providing recommendations before any purchase or endeavor. There are many key players like TripAdvisor, makemytrip, Airbnb, Google, Netflix, Hotstar, Wynk, Amazon, flipkart, and many more. These sites also provide recommendation to users to help them make a choice in terms of selecting websites, movies, products, and many more. In this chapter, the authors discuss different techniques used by recommender systems and the issues faced by them. The authors have also proposed techniques or strategies to deal with such issues. The use of artificial intelligence techniques besides the existing techniques, like classification or clustering, is also discussed.
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