A novel recommender system for adapting single machine problems to distributed systems within MapReduce
| dc.contributor.author | Orynbekova K. | |
| dc.contributor.author | Kadyrov Sh. | |
| dc.contributor.author | Bogdanchikov A. | |
| dc.contributor.author | Oktamov S. | |
| dc.date.accessioned | 2025-08-13T08:18:26Z | |
| dc.date.available | 2025-08-13T08:18:26Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | 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. | |
| dc.identifier.citation | Orynbekova K , Kadyrov Sh ,Bogdanchikov A , Oktamov S /A novel recommender system for adapting single machine problems to distributed systems within MapReduce / Bulletin of Electrical Engineering and Informatics / 2024 | |
| dc.identifier.issn | 2302-9285 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1877 | |
| dc.language.iso | en | |
| dc.publisher | Bulletin of Electrical Engineering and Informatics | |
| dc.subject | Distributed system | |
| dc.subject | Knowledge-based approach | |
| dc.subject | Machine learning model | |
| dc.title | A novel recommender system for adapting single machine problems to distributed systems within MapReduce | |
| dc.type | Article |