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Bogdanchikov, Andrey
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Electrical & Electronics Engineering

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A novel recommender system for adapting single machine problems to distributed systems within MapReduce Orynbekova, Kamila; Kadyrov, Shirali; Bogdanchikov, Andrey; Oktamov, Saidakmal
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.8370

Abstract

This research introduces a novel recommender system for adapting single-machine 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.
Co-Authors Kadyrov, Shirali Oktamov, Saidakmal Orynbekova, Kamila