AI-ENHANCED WEB SCRAPING FOR DATA-DRIVEN ANALYSIS

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Выпуск: Том 2 № 11 : Центральноазиатский журнал междисциплинарных исследований и исследований в области управления
Раздел: Статьи
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This article explores the synergy between web scraping techniques and artificial intelligence in extracting, processing, and analyzing large-scale online data. By combining traditional scraping tools with machine learning models, such as transformers and named entity recognition systems, the study demonstrates how raw web data can be transformed into actionable insights. The proposed pipeline was tested on real-world datasets, including news sites and product reviews. Results show significant improvements in data quality, classification accuracy, and analysis speed. This research offers a scalable framework for AI-powered online data mining.





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Как цитировать:

Shoykulov , S. . (2025). AI-ENHANCED WEB SCRAPING FOR DATA-DRIVEN ANALYSIS . Центральноазиатский журнал междисциплинарных исследований и исследований в области управления, 2(11), 20–27. извлечено от https://in-academy.uz/index.php/cajmrms/article/view/64810

Библиографические ссылки:

Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. NAACL-HLT.

Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., ... & Stoyanov, V. (2019). RoBERTa: A robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692.

Tjoa, E., & Guan, C. (2021). Web scraping tools: A comparative study. Web Technologies Journal, 14(2), 45–52.

Munz, M. (2020). Ethical considerations in web scraping. Journal of Internet Law, 24(1), 19–25.

Gupta, A., et al. (2022). Automated product insight mining from online reviews using hybrid scraping and deep learning. Applied Intelligence, 52(4), 3001–3015.

Shoyqulov Sh.Q. Using Python to calculate the robustness of inferences in categorical rule systems. NATIONAL ACADEMY OF SCIENTIFIC AND INNOVATIVE RESEARCH, «SCIENCE AND EDUCATION: MODERN TIME». (VOLUME 1 ISSUE 10, 2024), ISSN 3005-4729 / e-ISSN 3005-4737

Shoyqulov Sh.Q. Modern methods and means of protecting information on the Internet. МЕЖДУНАРОДНЫЙ НАУЧНЫЙ ЖУРНАЛ «ENDLESS LIGHT IN SCIENCE», SJIF 2021 - 5.81. 2022 - 5.94, октябрь 2024 г. Туркестан, Казахстан,

Shoyqulov Sh.Q. Analysis and optimization of graphics programming in C# using Unity. «Science and innovation» xalqaro ilmiy jurnali, Volume 3 Issue 10,

Shoyqulov Sh.Q. Main Internet threats and ways to protect against them. Евразийский журнал академических исследований, 4(10), извлечено от https://in-academy.uz/index.php/ejar/article/view/38709

Shoyqulov Sh.Q. Using Python programming in computer graphics. «Science and innovation» xalqaro ilmiy jurnali, Volume 3 Issue 10

Shoyqulov Sh.Q. Data visualization in Python, EURASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES (Т. 4, Выпуск 10, сс. 15–22).

Shoyqulov Sh.Q. Graphical programming of 2D applications in C#. EURASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES (Т. 4, Выпуск 10, сс. 7–14).

Shoyqulov Sh.Q. Methods for plotting function graphs in computers using backend and frontend internet technologies. Published in European Scholar Journal (ESJ). Spain, Impact Factor: 7.235, https://www.scholarzest.com, Vol. 2 No. 6, June 2021, ISSN: 2660-5562.

Shoyqulov Sh.Q. Multimedia possibilities of Web-technologies. Eurasian journal of mathematical, theory and computer sciences, UIF = 8.3 , SJIF = 5.916, ISSN 2181-2861, Vol. 3 Issue 3, Mart 2023, p. 11-15