This study presents a real-world collaborative filtering recommendation system implemented
in a large Korean fashion company that sells fashion products through both online and …

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

Parkinson's disease (PD) is a member of a larger group of neuromotor diseases marked by
the progressive death of dopamineproducing cells in the brain. Providing computational …

Abstract Predicting Unified Parkinson's Disease Rating Scale (UPDRS) in Total-UPDRS and
Motor-UPDRS clinical scales is an important part of controlling PD. Computational …

The importance of recommendation systems for business applications has led to extensive
research efforts to improve the recommendations accuracy as well as to reduce the sparsity …

Many approaches have been tried for the classification of arrhythmia. Due to the dynamic
nature of electrocardiogram (ECG) signals, it is challenging to use traditional handcrafted …

As a chronic disease, diabetes mellitus has emerged as a worldwide epidemic. Providing
diagnostic aid for diabetes disease by using a set of data that contains only medical …

This paper addresses the problem of multi-criteria recommendation in the hotel industry. The
main focus is to analyze user preferences from different aspects based on multi-criteria …

As a chronic disease, diabetes mellitus has emerged as a worldwide epidemic. The aim of
this study is to classify diabetes disease by developing an intelligence system using …

Recommender Systems are useful information filtering tools that have reduced information
overload over the web. Collaborative filtering (CF) is one of the extensively used …