Recommender System Using K-Nearest Neighbors and Singular Value Decomposition Algorithms: A Hybrid Approach

  • Rounick PalitEmail author
  • Rajdeep ChatterjeeEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1119)


Recommender systems have found their importance in many parts of our life, from helping us decide what product to buy next to helping us discover songs of different genres. This article provides some basics of recommender systems and how to implement them using content and collaborative-based filtering methods. The model takes a matrix of user ratings for books as input and top recommendations are generated. It also discusses hybrid or mixed recommender systems and how they can provide better recommendations to users. It identifies areas that need enhancement for future implementation.


Recommender system K-Nearest Neighbors Singular Value Decomposition Correlation 


  1. 1.
    Pennock, D.M., Horvitz, E., Lawrence, S., Giles, C.L.: Collaborative filtering by personality diagnosis: a hybrid memory- and model-based approach. In: Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI-2000), pp. 473–480. Morgan Kaufman, San francisco (2000)Google Scholar
  2. 2.
    Khan, B.M., Mansha, A., Khan, F.H., Bashir, S.: Collaborative filtering based online recommender system: a survey. In: International Conference on Information and Communication Technologies (2017)Google Scholar
  3. 3.
    Pereira, C., Iyer, S., Raut, C.: Recommendation system based on cosine similarity algorithm. Int. J. Recent. Trends Eng. Res. 3(9) (2017). ISSN: 2455-1457Google Scholar
  4. 4.
    Kathait, S.S., Tiwari, S., Singh, P.K.: Intelligent recommendation system. Int. J. Adv. Res., February (2017)Google Scholar
  5. 5.
    Jannach, D., Zanker, M., Felfernig, A., Friedrich, G.: Recommender Systems—An Introduction. Cambridge University Press (2011)Google Scholar
  6. 6.
    Leskovec, J., Rajaraman, A., Ullman, J.D.: Mining of Massive Datasets. Cambridge University Press (2011)Google Scholar
  7. 7.
    Burke, R.: Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction, November (2017)Google Scholar
  8. 8.
    Wen, Z.: Recommendation System Based on Collaborative Filtering. Technical Report, CS229, Stanford University, USA, December (2008)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.KIIT UniversityBhubaneswarIndia

Personalised recommendations