| Issue |
E3S Web Conf.
Volume 613, 2025
XI International Conference on Advanced Agritechnologies, Environmental Engineering and Sustainable Development (AGRITECH-XI 2025)
|
|
|---|---|---|
| Article Number | 03005 | |
| Number of page(s) | 5 | |
| Section | Digital Technologies and Automation in Agriculture | |
| DOI | https://doi.org/10.1051/e3sconf/202561303005 | |
| Published online | 07 February 2025 | |
Neural network technologies for identifying and ranking monitoring indicator values in agricultural universities
1 «Expert and Analytical Center», 33, Talalikhina str., Moscow, 109316, Russia
2 Reshetnev Siberian State University of Science and Technology, 31, Krasnoiarskii Rabochii Prospekt, Krasnoyarsk, 660037, Russia
3 Sevastopol State University, 33, University str., Sevastopol, 299053, Russia
* Corresponding author: kartsan2003@mail.ru
The topic under consideration, text classification using neural network technologies has significant potential in various industries, including universities of agriculture. Monitoring of key indicators is extremely important, but performing it manually with the involvement of experts can be costly and time-consuming compared to using neural network technologies for text processing. We analyzed natural language document classification and processing algorithms that are widely used in the development of voice assistants, chatbots, and smart home devices. The analysis of existing techniques for classifying natural language texts based on their content allowed us to identify the most effective methods for processing documents with complex and general problem formulation.
© The Authors, published by EDP Sciences, 2025
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