Recommender systems have become exceptionally widespread in recent years to deal with
the information overload problem by providing personalized recommendations. Multi-criteria …

Abstract In Recommendation Systems (RS) and Collaborative Filtering (CF), the similarity
measures have been the operating component upon which CF performance is essentially …

In recent years, collaborative filtering (CF) techniques have become one of the most
popularly used techniques for providing personalized services to users. CF techniques …

The Internet is changing the method of selling and purchasing items. Nowadays online
trading replaces offline trading. The items offered by the online system can influence the …

Personalized recommendation is a technical means to help users quickly and efficiently
obtain interesting content from massive information. However, the traditional …

Over the last decade, the growth of e-recruitment has resulted in the expansion of web
channels dedicated to candidate recruitment, making it easy to find and apply for jobs …

Virtual reality, as a medium that combines computer technology, imaging technology, and
human-computer interaction technology, not only brings a new interactive narrative method …

Purpose This study aims to introduce a novel rank aggregation algorithm that leverages
graph theory and deep-learning to improve the accuracy and relevance of aggregated …

While recommender systems have shown success in many fields, accurate
recommendations in industrial settings remain challenging. In maintenance, existing …

The shift towards Industry 4.0 has pushed many companies to adopt a digital system. With
the sheer amount of data available today, companies start to face difficulties with providing …