An application-oriented review of deep learning in recommender systems

Автор: Jyoti Shokeen, Chhavi Rana

Журнал: International Journal of Intelligent Systems and Applications @ijisa

Статья в выпуске: 5 vol.11, 2019 года.

Бесплатный доступ

The development in technology has gifted huge set of alternatives. In the modern era, it is difficult to select relevant items and information from the large amount of available data. Recommender systems have been proved helpful in choosing relevant items. Several algorithms for recommender systems have been proposed in previous years. But recommender systems implementing these algorithms suffer from various challenges. Deep learning is proved successful in speech recognition, image processing and object detection. In recent years, deep learning has been also proved effective in handling information overload and recommending items. This paper gives a brief overview of various deep learning techniques and their implementation in recommender systems for various applications. The increasing research in recommender systems using deep learning proves the success of deep learning techniques over traditional methods of recommender systems.

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Recommender system, Deep learning, Collaborative filtering, Deep neural network, Social recommender system

Короткий адрес: https://sciup.org/15016595

IDR: 15016595 | DOI: 10.5815/ijisa.2019.05.06

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