Recommending points of interest (POI) is a challenging task that requires extracting comprehensive location data from location-based social media platforms. To provide effective recommendations, it important to analyze users’ historical behavior and preferences. In this study, we present sophisticated location-aware recommendation system uses Bidirectional Encoder Representations Transformers (...

Advances in telecommunications and information technology have allowed the proliferation of mobile and multifunctional devices and their incorporation more and more into physical objects, making new information and services available. A consequent problem of this new scenario is information overload, i.e. users face vast and distributed information sources, and have difficulty in selecting thos...

A recommender system aims to recommend items that a user is interested in among many items. The need for the recommender system has been expanded by the information explosion. Various approaches have been suggested for providing meaningful recommendations to users. One of the proposed approaches is to consider a recommender system as aMarkov decision process (MDP) problem and try to solve it us...

The enormity of the amount of learning materials in e-learning has led to the difficulty of locating suitable learning materials for a particular learning topic, creating the need for recommendation tools within a learning context. In this paper, we aim to address this need by proposing a novel e-learning recommender system framework that is based on two conceptual foundations—peer learning and...

Shilling Attack Prevention for Recommender Systems Using Social-based Clustering Tak Man Desmond Lee A Recommender System (RS) is a system that utilizes user and item information to predict the feeling of users towards unfamiliar items. Recommender Systems have become popular tools for online stores due to their usefulness in confidently recommending items to users. A popular algorithm for reco...