Browsing by Author "Oktamov S."

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    A novel recommender system for adapting single machine problems to distributed systems within MapReduce
    (Bulletin of Electrical Engineering and Informatics, 2024) Orynbekova K.; Kadyrov Sh.; Bogdanchikov A.; Oktamov S.
    This research introduces a novel recommender system for adapting singlemachine problems to distributed systems within the MapReduce (MR) framework, integrating knowledge and text-based approaches. Categorizing common problems by five MR categories, the study develops and tests a tutorial with promising results. Expanding the dataset, machine learning models recommend solutions for distributed systems. Results demonstrate the logistic regression model's effectiveness, with a hybrid approach showing adaptability. The study contributes to advancing the adaptation of single-machine problems to distributed systems MR, presenting a novel framework for tailored recommendations, thereby enhancing scalability and efficiency in data processing workflows. Additionally, it fosters innovation in distributed computing paradigms.