Jyoti Shokeen

Mrs. Jyoti Shokeen

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 January 2019 in Artificial Intelligence Review
Verified
Journal Article
Closed access
PDF file
JSJyoti Shokeen
Jyoti Shokeen
CRChhavi Rana
Chhavi Rana

15 November 2019 in Journal of Intelligent Information Systems
Verified
Journal Article
Closed access
PDF file
JSJyoti Shokeen
Jyoti Shokeen
CRChhavi Rana
Chhavi Rana

17 May 2022 in The Journal of Supercomputing
Verified
Journal Article
Closed access
PDF file
PRPoonam Rani
Poonam Rani
PKPreeti Kaur
Preeti Kaur
VJVibha Jain
Vibha Jain
JSJyoti Shokeen
Jyoti Shokeen
SNSweety Nain
Sweety Nain

20 May 2022 in Journal of Ambient Intelligence and Humanized Computing
Verified
Journal Article
Closed access
PDF file
PRPoonam Rani
Poonam Rani
VJVibha Jain
Vibha Jain
JSJyoti Shokeen
Jyoti Shokeen
ABArnav Balyan
Arnav Balyan

2 January 2021 in Journal of Ambient Intelligence and Humanized Computing
Verified
Journal Article
Closed access
PDF file
JSJyoti Shokeen
Jyoti Shokeen
CRChhavi Rana
Chhavi Rana

8 May 2019 in International Journal of Intelligent Systems and Applications
Verified
Journal Article
Open access
PDF file
JSJyoti Shokeen
Jyoti Shokeen
CRChhavi Rana
Chhavi Rana
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.