Work place: Department of CSE, UIET, M.D. University, Rohtak, 124001, India
E-mail: jyotishokeen12@gmail.com
Website:
Research Interests: Computer Networks, Information Systems, Multimedia Information System, Social Information Systems, Information Theory, Algorithmic Information Theory
Biography
Jyoti Shokeen belongs to Delhi. She is a Research Scholar in Department of Computer Science and Engineering, University Institute of Engineering and Technology, Maharshi Dayanand University, Rohtak, Haryana. She works under the guidance of Dr. Chhavi Rana. She received her M.Tech degree in CSE in 2014. Her research areas include Social networks, Information Retrieval and Machine learning.
She has published a number of research papers in International Journals. She has also published several papers in IEEE and Springer conferences.
DOI: https://doi.org/10.5815/ijisa.2019.05.06, Pub. Date: 8 May 2019
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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