Collaborative filtering (CF)-based recommenders work by estimating a user's potential
preferences on unobserved items referring to the other users' observed preferences. Slope …

Mobile tourism or m-tourism can assist and help tourists anywhere and anytime face the
overload of information that may appear in their smartphones. Indeed, these mobile users …

Collaborative Filtering (CF) is one of the most widely applied and effective techniques in the
Recommendation Systems (RSs). A CF method recommends a set of items to a target user …

The recommendation selected data from hundreds of entries to get reliable and accurate
information that is just learning to predict unknown information. Weighted slope one which is …

Recommender System is useful tool for providing personalized suggestion to users.
Collaborative filtering is one of the major and popular techniques for recommender system …

Collaborative filtering (CF) is a traditional and popular technique in the recommendation
system (RS) paradigm. Notably, one specific form of item-based collaborative filtering …

This paper proposes a novel weight-enriched ranking-based baseline model,
WeightedSLIM, aiming to provide more accurate top-N recommendations from implicit user …

Collaborative filtering (CF) framework in recommendation is a very popular technique for
providing personalized recommendation. Slope one predictor is a model-based CF which …

Assessing quality of products, especially when purchased online, is always a challenge.
One of the widely used approaches for addressing this challenge is to rely on the scores …

Recommender systems have been developed to address the “information overload” issue
by providing users with potentially useful products or services. While most of the current …