Browsing by Author "Orynbekova K."
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Item Open Access 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.Item Open Access ANALYSIS OF THE KAZAKH CYBER TOURNAMENTS PLATFORM “PINGER.KZ”(СДУ хабаршысы - 2023, 2023) Alimanova M.; Karazhar B. ; Alseitova A. ; Orynbekova K.Abstract. Worldwide experts presume further growth of videogames field and suggest solutions according to the actual statistics. Despite the remarkable successes of the e-athletes from Kazakhstan in a worldwide arena, there is a lack of statistical data on the local cybersport. Therefore, the research was conducted to provide prospective researchers in fields like gamification, eSport and media with actual data. The given scientific paper uses the data collected and analysed from the largest cyber tournament platform in Kazakhstan “Pinger.kz”. The analysed information is about tournaments that took place since the website launched in 2019 to 2021. The libraries of Python for data analysis as BeautifulSoup, requests, matplotlib and Apache tools were used. The aim of the work is to collect and make data analysis for future research. The paper identifies the most popular games among kazakh players in order to use this data in the research on gamification. Parsed data results show the development of the local cybersport and confirm worldwide trends.Item Open Access Defining Semantically Close Words of Kazakh Language with Distributed System Apache Spark(MDPI, 2023) Ayazbayev D.; Bogdanchikov A.; Orynbekova K.; Varlamis I.This work focuses on determining semantically close words and using semantic similarity in general in order to improve performance in information retrieval tasks. The semantic similarity of words is an important task with many applications from information retrieval to spell checking or even document clustering and classification. Although, in languages with rich linguistic resources, the methods and tools for this task are well established, some languages do not have such tools. The first step in our experiment is to represent the words in a collection in a vector form and then define the semantic similarity of the terms using a vector similarity method. In order to tame the complexity of the task, which relies on the number of word (and, consequently, of the vector) pairs that have to be combined in order to define the semantically closest word pairs, A distributed method that runs on Apache Spark is designed to reduce the calculation time by running comparison tasks in parallel. Three alternative implementations are proposed and tested using a list of target words and seeking the most semantically similar words from a lexicon for each one of them. In a second step, we employ pre-trained multilingual sentence transformers to capture the content semantics at a sentence level and a vector-based semantic index to accelerate the searches. The code is written in MapReduce, and the experiments and results show that the proposed methods can provide an interesting solution for finding similar words or texts in the Kazakh language.Item Open Access Development of system automating of sorting letters at the post office(2017) Orynbekova K.Development of postal service starts from 6 thousand years BC. Actually, first messages were send and service starts later, but these tam-tam drums laid the foundation of post service. During evolution of humanity people met problems, and then they tried to find solutions, such a smoke camp fire or pigeon. Time decreasing consumption system proposes the most optimal rack to Store the package, optimal by size and distance between rack and delivery stake. Algorithm is intended to decrease time for searching the empty racks and the racks, which have been already, stored the packages. It will make delivery and sorting process at receiving much faster and also will optimize consuming free space in racks, Automating sorting algorithm is a system, which proposes the most optimal rack to store the package, optimal by size and distance between rack and delivery stake. Algorithm is intended to decrease time for searching the empty racks and the racks, which have been already, stored the packages. It will make delivery and sorting process at receiving much faster and also will optimize consuming free space in racks. During delivery, post official will exactly know, in which rack does the package stored and during sorting, it wouldn't be necessary to look for optimized rack to place package; in case if post official will not look for optimized rack, optimized consumption of space will not be actual. In developing of algorithm Mathematics and Statistics Science were used. And there are intentions for developing algorithm, working with Internet of Things methodology in future.Item Open Access MapReduce Solutions Classification by Their Implementation(The International Journal of Engineering Pedagogy (iJEP), 2023) Orynbekova K.; Bogdanchikov A.; Cankurt S.; Adamov A.; Kadyrov Sh.Distributed Systems are widely used in industrial projects and scientific research. The Apache Hadoop environment, which works on the MapReduce paradigm, lost popularity because new, modern tools were developed. For example, Apache Spark is preferred in some cases since it uses RAM resources to hold intermediate calculations; therefore, it works faster and is easier to use. In order to take full advantage of it, users must think about the MapReduce concept. In this paper, a usual solution and MapReduce solution of ten problems were compared by their pseudocodes and categorized into five groups. According to these groups’ descriptions and pseudocodes, readers can get a concept of MapReduce without taking specific courses. This paper proposes a five-category classification methodology to help distributed-system users learn the MapReduce paradigm fast. The proposed methodology is illustrated with ten tasks. Furthermore, statistical analysis is carried out to test if the proposed classification methodology affects learner performance. The results of this study indicate that the proposed model outperforms the traditional approach with statistical significance, as evidenced by a p-value of less than 0.05. The policy implication is that educational institutions and organizations could adopt the proposed classification methodology to help learners and employees acquire the necessary knowledge and skills to use distributed systems effectively.Item Open Access MBTI personality classification using Apache Spark(ResearchGate, 2021) Orynbekova K.; Talasbek A.; Omar A.Personality determines how person make decisions, speak or react on different situations. In this paper explained shortly the specifics of Myers-Briggs Type Indicator personality classification, then details of preparation of the experiment to run on Apache Spark platform. In experiment three different classification algorithms (Logistic Regression, Naive Bayes, Support Vector Machine) are used to train and predict MBTI personality pairs on a Kaggle dataset consisting of 8675 users tweets. In the end explained the data preprocessing and algorithm training, testing, validation details and results. The models with different vector combinations have been compared, and results have been described.