Matrix-factorization (MF)-based approaches prove to be highly accurate and scalable in
addressing collaborative filtering (CF) problems. During the MF process, the non-negativity …

A recommender system (RS) is a data filtering technique that suggests the appropriate
information to the end-user. Collaborative filtering is the most frequently deployed algorithm …

Collaborative filtering systems are vulnerable to shilling attacks or profile injection attacks in
which malicious users can deliberately manipulate the systems' recommendation output by …

Recommendation systems are tools of option used to select the data relevant to a given user
from online sources. Collaborative filtering (CF) could be the most thriving approach to build …

Collaborative filtering is a popular strategy in recommender systems area. This approach
gathers users' ratings and then predicts what users will rate based on their similarity to other …

With restaurant menus becoming vast and dish names complicated, we present a
recommendation system to facilitate ordering food at restaurants. The design approach is …

Mining methods selection (MMS) is one of the most critical and complex decision-making
tasks in mine planning. The selection of underground mining methods is considered to be …

The “sparsity” challenge is a well-known problem in recommender systems. This issue
relates to little information about each user or item in large data set. The purpose of this …

Traditionally, Collaborative Filtering (CF) based recommendation employs past rating
behaviors of users on items to discover similar users and similar items. We can further …

One of the great challenges in modern biology is understanding the genome and its
translation into biological structures and function. In this context, the aim of this dissertation …