A substantial progress in development of new and efficient tensor factorization techniques
has led to an extensive research of their applicability in recommender systems field. Tensor …

Incorporating contextual information in recommender systems is an effective approach to
create more accurate and relevant recommendations. This review has been conducted to …

In today's digital world, it has become an irksome task to find the content of one's liking in an
endless variety of content that are being consumed like books, videos, articles, movies, etc …

Abstract In the Artificial Intelligence (AI) field, and particularly within the area of Machine
Learning (ML), recommender systems have attracted significant research attention. These …

Online hotel searching is a daunting task due to the wealth of online information. Reviews
written by other travelers replace the word-of-mouth, yet turn the search into a time …

Context-aware recommender system (CARS) is a highly researched and implemented way
of providing a personalized service that helps users to find their desired content. One of the …

Recommender systems often generate recommendations based on user's prior preferences.
Users' preferences may change over time due to user mode change or context change …

Recommender systems are important building blocks in many of today's e-commerce
applications including targeted advertising, personalized marketing and information …

Recommendation systems are specialized in offering suggestions about specific items of
different types (eg, books, movies, restaurants, and hotels) that could be interesting for the …

With the prevalence of mobile devices such as smartphones and tablets, the ways people
access to the Internet have changed enormously. In addition to the information that can be …