Recommendation systems are gaining increasing popularity in many application areas like
e-commerce, movie and music recommendations, tourism, news, advertisement, stock …

The data sparsity is an acute challenge in most of the collaborative filterings (CFs) as their
performance is affected by the known ratings of target users. Recently, active learning has …

Ant colony optimization (ACO) is a well-explored meta-heuristic algorithm, among whose
many applications feature selection (FS) is an important one. Most existing versions of ACO …

Collaborative filtering (CF) is a widely applied method to perform recommendation tasks in a
wide range of domains and applications. Dictionary learning (DL) models, which are highly …

The creation of digital marketing has enabled companies to adopt personalized item
recommendations for their customers. This process keeps them ahead of the competition …

Level of Trust can determine which source of information is reliable and with whom we
should share or from whom we should accept information. There are several applications for …

In recent years, the use of trust-based recommendation systems to predict the scores of
items not rated by users has attracted many researchers' interest. Accordingly, they create a …

To solve the problem of falling into local optimum and poor convergence speed in large
Traveling Salesman Problem (TSP), this paper proposes a Pearson correlation coefficient …

With the increase in the use of mobile devices having location-related capabilities, the use of
Location-Based Social Networks (LBSN) has also increased, allowing users to share …

Due to its successful application in information filtering and knowledge retrieval systems in
the era of big data, personalized recommender system plays a significant role in meeting …