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Recommendation System Based on Deep Learning

  • Tianhan GaoEmail author
  • Lei JiangEmail author
  • Xibao Wang
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 97)

Abstract

With the exponential growth of digital resource from Internet, search engines and recommendation systems have become the effective way to find relevant information in a short period of time. In recent years, advances in deep learning have received great attention in the fields of speech recognition, image processing, and natural language processing. The recommendation system is an important technology to alleviate information overload. How to integrate deep learning into the recommendation system, use the advantages of deep learning to learn the inherent essential characteristics of users and items from various complex multi-dimensional data, and build a model that more closely matches the user’s interest needs has become a hotpot in the research field. This paper reviews the research and application status of recommendation algorithms based on deep learning, and tries to discusses and forecasts the research trends of deep learning approaches applied to recommendation systems. proceedings.

Notes

Acknowledgement

This paper is supported by China Fundamental Research Funds for the Central Universities under Grant No. N180716019 and Grant No. N182808003.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Liaoning Research Center of Safety Engineering Technology in Industrial ControlNortheastern UniversityShenyangChina
  2. 2.Northeastern UniversityShenyangChina
  3. 3.Dalian University of TechnologyDalianChina

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