Matrix Factorization (MF) is one of the most popular techniques used in Collaborative
Filtering (CF) based Recommender System (RS). Most of the MF methods tend to remove …

Today, recommendation algorithms are widely used by companies in multiple sectors with
the aim of increasing their profits or offering a more specialized service to their customers …

A recommender system primary purpose is to provide a series of item suggestions on a topic
to its user. Deep learning is used in many fields and solved difficult and complex problems …

Nowadays, Information and communications technology (ICT) becomes a very important
thing in human life in different fields. They are used in many fields as information systems …

Saving time is one of the most important things. A Recommender system certainly saves our
time by generating a prediction of things for us from an extensive database that we might …

Recommendation system is currently attracting the interest of many explorers. Various new
businesses have surfaced with the rise of online marketing (E-Commerce) in response to …

Recommender systems are used to make recommendations about products, information, or
services for users. Most existing recommender systems implicitly assume one particular type …

A general theory of resource-bounded measurability and measure is developed. Starting
from any feasible probability measure/spl nu/on the Canter space C (the set of all decision …

Personalized recommendation for knowledge reuse provides a framework to share product
knowledge such as assembly process, environmental impact and energy efficiency in …

The fundament of data mining (DM) is to analyses data from various points of view. Classify
the data and summarize it, DM has begun to be widespread in every and each application …