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Analysis Of User Behavior In Information Search Systems Design Of Recommendation Systems

Authors

  • Go'zal Ravshanovna Khurramova

    Shahriasbz State Pedagogical Education and Training Theory and Methodology (Preschool Education Direction) 1.25-Group Master's Student
    Author

Keywords:

recommender systems, user behavior, information retrieval, collaborative filtering, content-based filtering, implicit data.

Abstract

This article examines the issues of analyzing user behavior (clicks, dwell time, search queries, etc.) in information retrieval and recommender systems. The paper analyzes methods for collecting implicit and explicit data, as well as the role of machine learning algorithms in generating personalized recommendations.

References

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Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix Factorization Techniques for Recommender Systems. Computer, 42(8), 30-37.

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Additional Files

Published

2026-04-02

How to Cite

Khurramova, G. R. (2026). Analysis Of User Behavior In Information Search Systems Design Of Recommendation Systems. International Conference on Global Trends and Innovations in Multidisciplinary Research, 2(2(B), 235-237. https://www.tlepub.org/index.php/2/article/view/900