The week's pick
Reseach Article
Deep Learning Innovations in Recommender Systems
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 12 |
| Year of Publication: 2019 |
| Authors: Bilal Ahmed, Li Wang, Muhammad Amjad, Waqar Hussain, Syed Badar-ud-Duja, M. Abdul Qadoos Bilal |
10.5120/ijca2019918882
|
Bilal Ahmed, Li Wang, Muhammad Amjad, Waqar Hussain, Syed Badar-ud-Duja, M. Abdul Qadoos Bilal . Deep Learning Innovations in Recommender Systems. International Journal of Computer Applications. 178, 12 ( May 2019), 57-59. DOI=10.5120/ijca2019918882
Abstract
Recommender systems are one of the best choices to cope with the problem of information overload. These systems are commonly used in recent years help to match users with different items. As more data is available on the internet traditional methods suffer from challenges like accuracy and scalability. Deep learning a state of art machine learning method also achieve promising performance in the field of recommender system. In this study we provide an overview of traditional approaches their limitations and then discuss about the aspects of deep learning used in the recommender system domain to improve the accuracy in recommender system domains. These deep recommender systems can be used to understand the demands of users and improve the value in recommendations.
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