Articles

FUNCTIONS OF RECOMMENDER SYSTEMS

Vol. 2 No. 5 (2022): Eurasian Journal of Academic Research 15-19

DOI: 10.5281/zenodo.6528923 2022-05-10 Articles CC BY 4.0 Open Access

Authors

  • Sherzod Khushbakov Student of TUIT FSE
  • Mansur Khamraev Student of TUIT FSE
  • Mokhiruy Bakhtiyorova Student of TUIT FSE

Abstract

On the Internet, where the number of choices is overwhelming, there is need to filter, prioritize and efficiently deliver relevant information in order to alleviate the problem of information overload, which has created a potential problem to many Internet users. Recommender systems solve this problem by searching through large volume of dynamically generated information to provide users with personalized content and services. This paper explores the different function of recommendation systems in order to serve as a compass for research and practice in the field of recommendation systems.

Keywords:

References

J. Bobadilla, F. Ortega, A. Hernando, A. Gutiérrez, Recommender systems survey, Knowledge-Based Systems, 46 (2013) 109-132.

L. Quijano-Sanchez, J.A. Recio-Garcia, B. Diaz-Agudo, G. Jimenez-Diaz, Social factors in group recommender systems, ACM Transactions on Intelligent Systems and Technology (TIST), 4 (2013) 1-30.

Bortko, K.; Bartków, P.; Jankowski, J.; Kuras, D.; Sulikowski, P. Multi-criteria Evaluation of Recommending Interfaces towards Habituation Reduction and Limited Negative Impact on User Experience. Procedia Comput. Sci. 2019, 159, 2240–2248.

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    Published

    2022-05-10

    How to Cite

    Khushbakov , S., Khamraev , M., & Bakhtiyorova , M. (2022). FUNCTIONS OF RECOMMENDER SYSTEMS. Eurasian Journal of Academic Research, 2(5), 15-19. https://doi.org/10.5281/zenodo.6528923
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