Collaborative filtering recommender systems (CFRSs) have already been proved effective to
cope with the information overload problem since they merged in the past two decades …

Nowadays, due to the increasing amount of data, the use of recommender systems has
increased. Therefore, the quality of the recommendations for the users of these systems is …

Given the increasing growth of the Web and consequently the growth of e-commerce, the
amount of data which users face are increasing day by day. Therefore, one of the key issues …

Shilling attacks have been a significant vulnerability to collaborative filtering based
recommender systems recently. There are various studies focusing on detecting shilling …

With recent advances in e-commerce platforms, the information overload has grown due to
increasing number of users, rapid generation of data and items in the recommender system …

Recommendation systems can suggest users list of items they have not yet seen but might
be interested in. To improve the quality of the generated recommendations, different …

Sažetak In recent times, we have loads and loads of information available over the Internet.
It has become very cumbersome to extract relevant information out of this huge amount of …

The Recommendation system relies on feedback and personal information collected from
users for effective recommendation. The success of a recommendation system is highly …

Recommender system (RS) in the present web environment is required to gain the
knowledge of the users and their commitments such as like and dislike about any items …

ABSTRACT E-Commerce recommender systems are affected by various kinds of profile-
injection attacks where several fake user profiles are entered into the system to influence the …