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

Abstract Group Point-of-Interests (POI) recommendation devotes to find the optimal POIs for
groups, which has extracted extensive attention. This work first brings forward a novel POI …

Interest in smart green cities is growing, and IoT is an underlying driver of this trend. The
integration of IoT in smart cities has altered the manner of working and living of society. IoT …

Tourism is vital to national economic growth and fulfilling individuals' spiritual pursuits.
However, traditional scenic recommendation algorithms must improve accuracy …

In recent years, commercial platforms have embraced recommendation algorithms to
provide customers with personalized recommendations. Collaborative Filtering is the most …

Most research on movie recommender systems has been conducted with Collaborative
Filtering (CF) methods. The lack of sufficient information about users' interests in …

Recommender systems are developed to personalize services for each user. The focus of
recommender systems is to accurately discover the unknown preferences of users. To …

In recommendation systems, users often click on some items that are distinct from historically
clicked items. This verifies the existence of interest gaps between the historical interests …

Urban visual localization is the process of determining the pose (position and attitude) of the
imaging sensor (or platform) with the help of existing geo-referenced data. This task is …