Restaurant recommendation is one of the most interesting recommendation problems
because of its high practicality and rich context. Many works have been proposed to …

In this study, we utilize users' reviews to a restaurant recommender system to further explore
users' opinions by the proposed recommender approach. Considering the uncertainty of …

There are a lot of restaurants to pick from these days, so it might be difficult for folks to locate
a new location to eat. It can be challenging to choose one that precisely suits their …

On the internet, numerous options are available for a specific type of product. It is tough to
manually go through every product in a particular type when a user is trying to choose the …

User preferences are typically analyzed by recommendation systems for recommending
items. However, in most existing restaurant recommendation methods, recommendation …

To eliminate the concerns of cold-start and scalability within the filtering, collaborative
recommendation system for a hotel under the ranking list for the customer; this study …

Online recommendation service had brought economic benefits for traditional catering
industry. Aimed at the status quo, user-based collaborative filtering (UCF) algorithm was …

The constantly expanding volume of online information is a strategic approach to managing
the excessive amount of data. The importance of recommender systems cannot be …

Most users often find themselves in a situation when they need to answer the same
question: which product, movie, vacation offer, restaurant or book is the best to choose? In …

Recommender systems are algorithms for suggesting relevant items to users (items being
movies, books, products to buy or anything else depending on industries). By building up a …