Recommendation System is a major area which is very popular and useful for people to take
proper decision. It is a method that helps user to find out the information which is beneficial …

An essential goal of recommendation systems is to provide users with accurate and
personalized recommendations that meet their preferences. With the rapid growth of IoT …

Nowadays, the increasing demand for group recommendations can be observed. In this
paper we address the problem of recommendation performance for groups of users (group …

The new user problem is an important and challenging issue that Context-Aware
Recommender Systems (CARSs) must deal with, especially in the early stage of their …

How can we effectively recommend items to a user about whom we have no information?
This is the problem we focus on in this paper, known as the cold-start problem. In most …

In collaborative filtering recommender systems, items recommended to an active user are
selected based on the interests of users similar to him/her. Collaborative filtering systems …

Sequential user modeling, a critical task in personalized recommender systems, focuses on
predicting the next item a user would prefer, requiring a deep understanding of user …

With the increasing ubiquity of access to online news sources, the news recommender
systems are becoming widely popular in recent days. However, providing interesting news …

We propose a novel methodology for design error diagnosis in the HDL description using a
word-level solver. In this approach, the patterns that result in erroneous responses are first …

Context-Aware Recommender Systems (CARSs) suffer from the cold-start problem, ie, the
inability to provide accurate recommendations for new users, items or contextual situations …