Recommendation System: Overview, Current Applications and Future Scope

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Rahul Tilokani
Chetana Thaokar
Sarang Awale
Shubh Popat
Pratik Pudke

Abstract

The purpose of this research paper is to discuss areas of research, current trends and future scope of Recommendation
System. This paper talks about the functioning of Recommendation Systems, recent trends in IT involving use
of RS, approach to build an RS, scope of RS in future and issues associated with it. RS has become a widespread
tool in IT, used by leading Software companies. It has come out as a major subject in IT in the area of research;
Over thousand papers have been published on RS and has resulted in acquiring some interesting findings which
were later got implemented. This paper not only talks about the current applications but also provide a vision
towards its future scope. This research has included different areas where recommendation systems are currently
in use.

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How to Cite
Tilokani, R., Thaokar, C. ., Awale, S., Popat, S., & Pudke, P. (2021). Recommendation System: Overview, Current Applications and Future Scope. International Journal of Next-Generation Computing, 12(5). https://doi.org/10.47164/ijngc.v12i5.467

References

  1. Thi Ngoc Trang,Cristopher Trattner,Andreas Holzinger Recommender
  2. systems in the Healthcare Domain: State of the art and the research issues Journal of Intelligent Information Systems, August 2021
  3. Pradeep Singh, Pijush Pramanik, Avick Dey, Prasenjit Choudhary Recommender Systems: An Overview, Research Trends, and Future Directions International Journal of Business and System Research,January 2021 DOI: https://doi.org/10.1504/IJBSR.2021.10033303
  4. George Karypis, Xia Ning Recent Advances in Recommender Systems and Future Directions George Karypis Minnesota, the Conference: International Conference on Pattern Recognition and Machine Intelligence. June 2015, DOI:10.1007/978-3-319-19941-2 1 DOI: https://doi.org/10.1007/978-3-319-19941-2
  5. Sajal Haldar, Hanif Seddiqui An Entertainment Recommendation System using the Dynamics of User Behaviour over Time 17th International Conference on Computer and In formation Technology (ICCIT), Dhaka, Bangladesh, December 2014 DOI:10.1109/ICCITechn.2014.7073094 DOI: https://doi.org/10.1109/ICCITechn.2014.7073094
  6. G.Enriquez, LMorales,Fernando Alsono, Mayo Recommendation and Classification Systems Scientific Programming, Vol 2019, DOI: https://doi.org/10.1155/2019/8043905
  7. Joeran Beel1, Bela Gipp, Stefan Langer, Corinna Breitinger Researchpaper recommender systems: a literature survey International Journal on Digital Libraries.
  8. N. Agarwal, E. Haque, H. Liu, and L. Parsons Research paper recommender systems: A subspace clustering approach in International Conference on Web-Age Information Management, 2005. DOI: https://doi.org/10.1007/11563952_42
  9. Liu H., Kong X., Bai X., Wang W., Bekele T. M., and Xia F. Contextbased collaborative filtering for citation recommendation IEEE Access, vol. 3, pp. 1695–1703, 2015. DOI: https://doi.org/10.1109/ACCESS.2015.2481320
  10. A. Azaria, A. Hassidim, S. Kraus, A. Eshkol, O. Weintraub, and I. Netanely Movie recommender system for profit maximization in Proceedings of the 7th ACM conference on Recommender systems, 2013, pp. 121–128. DOI: https://doi.org/10.1145/2507157.2507162