Collaborative filtering (CF) based recommender systems have been proven to be a
promising solution to the problem of information overload. Such systems provide …

Personalization of user experience through recommendations involves understanding their
preferences and the context they are living in. In this work, we present a method to rank …

Content-based restaurant recommender systems use features such as cuisine type, price
range, and location to suggest dining options to users. Current research explores ways to …

Recommender Systems learn users' preferences and tastes in different domains to suggest
potentially interesting items to users. Group Recommender Systems generate …

W. SONG ET AL. COLLABORATIVE FILTERING WITH DATA CLASSIFICATION generate
recommendations based on user preferences. However, the CF method is vulnerable if no …

Recommender systems, also known as recommender engines, have become an important
research area and are now being applied in various fields. In addition, the techniques …

In this article we argue that the research on group recommender systems must look more
carefully at group dynamics in decision making in order to produce technologies that will be …

Designing (group) recommender systems in the travel and tourism domain is a difficult task,
considering the complexity and intangibility of a tourism product, ie,(i) it is a bundle of …

Recommender Systems (RS) have been increasingly common in web applications seeking
to predict content items of potential interest to users. Among others, RSs have been …

The opinions of people who previously experienced items are crucial to decision-making.
My Ph. D. research project is focused on finding a better way to recommend experience …