Publications
Talk · International Conference on Electronics, Computer and Computation · December 1, 2019
Distributed sentiment analysis of an agglutinative language via Spark by applying machine learning methods
Azamat Serek, Ainur Issabek, Andrey Bogdanchikov
Abstract
Currently there are a large amount of studies conducted on the field of sentiment analysis worldwide. Due to continuous drastic increase of amount of data, all natural language processing systems require special approach oriented to it. Implementing and evaluating such mechanism was a strong incentive to conduct this research. In this paper, sentiment analysis was implemented on Kazakh language via Spark on the basis of data set taken from Kazakh books. The data was initially unbalanced. There was achieved training F1 measure over 90 %.
Sentiment Analysis and Opinion MiningNatural Language Processing TechniquesTopic Modelingsentiment analysisKazakh languageagglutinative languages
More by Azamat Serek
- COMPARATIVE ANALYSIS OF MACHINE LEARNING METHODS FOR DETECTING FRAUD IN TEXT MESSAGESNEWS OF THE NATIONAL ACADEMY OF SCIENCES OF THE REPUBLIC OF KAZAKHSTAN · 2026
- EXPLAINABLE MULTISPECTRAL ATTENTION NETWORK FOR SENTINEL-2 AGRICULTURAL LAND CLASSIFICATIONScientific Journal of Astana IT University · 2026
- SEMANTIC SEGMENTATION OF AGRICULTURAL FIELD ANOMALY PATTERNS IN AERIAL IMAGES USING U-NETHerald of Kazakh-British technical university · 2026
- From Detection to Maps: A Review of Automated Urban Tree Mapping Using UAV and High-Resolution Satellite DataJournal of Imaging · 2026