Among the primary aims of Artificial Intelligence (AI) is the enhancement of User Experience
(UX) by providing deep understanding, profound empathy, tailored assistance, useful …

Collaborative Filtering (CF) has intrigued several researchers whose goal is to enhance
Recommender System's performance by mitigating their drawbacks. CF's common idea is to …

Recommender system is an information filtering tool used to alleviate information overload
for users on the web. Collaborative filtering recommends items to users based on their …

Collaborative filtering approach greatly promotes the development and application of
personalized recommendation. In location-based social networks (LBSNs), the sparsity of …

The increasing demand for personalized information has resulted in the development of the
Recommender System (RS). RS has been widely utilized and broadly studied to suggest the …

Collaborative filtering (CF), one of the most widely employed methodologies for
recommender systems, has drawn undeniable attention due to its effectiveness and …

Item-based filtering technique is a collaborative filtering algorithm for recommendations.
Correlation-based similarity measures such as cosine similarity, Pearson correlation, and its …

In recent years, collaborative filtering (CF) techniques have become one of the most
popularly used techniques for providing personalized services to users. CF techniques …

In recommender systems, Collaborative Filtering (CF) plays an essential role in promoting
recommendation services. The conventional CF approach has limitations, namely data …

As living data growing and evolving rapidly, traditional machine learning algorithms are hard
to update models when dealing with new training data. When new data arrives, traditional …