| ITI əməkdaşlarının elmi işləri - tezis |
| Biblioqrafik təsvir | |
| Alekberova , I.Y. Classification of Human Behavior Based on Text Data Using Support Vector Machine / I.Y. Alekberova // The XII International Conference on Computer Processing of Turkic Languages “TurkLang 2024”. - Kazan, 2024. - P. 149-153. | |
| Annotasiya | |
| In the contemporary landscape, information technology provides vast data and novel opportunities for analyzing human behavior. The accuracy of predicting human behavior largely depends on selecting appropriate data sources, as well as the methods and algorithms employed. Electronic demographic platforms, which aggregate and analyze user data from various online sources, offer a unique opportunity to forecast behavioral patterns through machine learning techniques. Machine learning algorithms have become essential tools for extracting insights from large datasets. This study focuses on the use of text data to analyze human behavior, with information drawn from three key sources: demographic data, scientific articles, various documents written by employees, and social media content. We propose using the support vector machine method to identify different behavioral categories. Support vector machine algorithms can handle diverse data types, making them an effective and adaptable tool in big data analytics. By classifying documents into relevant topics using support vector machines, it is possible to assess how employee behavior aligns with the performance criteria essential for their professional success. | |
| Elektron variant | |
| Elektron variant |
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