Deep-Learing based Recommendation System Survey Paper
Prakash Kumar K, V Vanitha · Zenodo (CERN European Organization for Nuclear Research) · 2022
With the proliferation of online information, recommender systems have shown to be an effective method of overcoming this information imbalance. The utility of recommendation systems cannot be overstated, as can their ability to ease several concerns associated with excessive choice. Deep learning has had a significant effect in recent years across a variety of research disciplines, including computer vision and natural language processing, contributing not only to astounding results but also to the alluring trait of learning feature representations from scratch. Deep learning's influence is equally ubiquitous, with research demonstrating its usefulness when utilised for recommender systems and information retrieval. The topic of deep learning in recommender systems appears to be growing. The purpose of this study is to provide an in-depth evaluation of recent research endeavours on deep-learning-based recommender systems. Simply put, we explain and categorise deep learning-based recommendation models, as well as provide a consistent appraisal of the research. Finally, we elaborate on current trends and give new perspectives on the industry's game-changing rise.