The use of artificial intelligence in database and knowledge sytems - an analysis of machine learning, neural networks, and other AI methods

Sep 17, 2026

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The use of artificial intelligence in database and knowledge systems is analyzed through machine learning, neural networks, and related AI methods for data and knowledge analysis. Machine learning is presented as enabling learning from data and discovering dependencies for prediction, recommendation, classification, and recognition. Neural networks and deep learning support text and language processing, including machine translation and sentiment analysis. Big Data is handled more efficiently via AI-driven analysis and personalized recommendation systems. The discussion extends to computer vision for automated analysis of images and videos, concluding with ethical and security considerations and future research directions.

LanguageEnglish

CategoryTechnology

FormatPDF

Pages4

Reading Time10 min

AccessFree to download

Machine Learning for Data and Knowledge Analysis

Prediction and Recommendations

Classification and Recognition

Neural Networks and Deep Learning in Text and Language Processing

Machine Translation

Sentiment Analysis

Handling Big Data with AI

Efficient Data Processing and Analysis

Personalized Recommendations

Applying AI for Automated Natural Data Processing

Computer Vision

AI-Based Recommendation Systems

Conclusion

References

Висновки . Розроблено програмне забезпечення сейсмологічної аналітичної системи, яка розділена на дві основні частини: підсистему вводу, зберіганнята управління даними та підсистему аналізу даних . Підсистема аналізу данихреалізована з використанням різних бібліотек машинного навчання для вирішення конкретних завдань у контексті системи .Список використаних літературних джерел [1] Элбон Крис . Машинное обучение с использованием Python. Сборникрецептов / – СПб: БХВ-Петербург, 2019.– 384 с . [2] Шамин Р.В . Практическое руководство по методам машинного обучения/ – М .: [Lector.ru](Lector.ru), 2019.– 93 с . [3] Завьялов А.Д . Среднесрочный прогноз землетрясений . Основы, методика,реализация / – М.: Наука, 2006.– 256 с . Oleh Haba assistant teacher of Computer Science Department, Ukrainian National Forestry University, Lviv, Ukraine, [https://orcid.org/0009-0006-2140-4524](https://orcid.org/0009-0006-2140-4524) . [oleh.haba@nltu.edu.ua](oleh.haba@nltu.edu.ua) The use of artificial intelligence in database and knowledge sytems-an analysis of machine learning, neural networks, and other ai methods for database and knowledge analysis Abstract-This presentation explores the use of artificial intelligence (AI) in database and knowledge systems, with a focus on the applications of machine learning, neural networks, and other AI methods for data and knowledge analysis. Machine learning allows computers to learn from data and make predictions, while neural networks excel in natural language processing. Processing large volumes of data with AI simplifies analysis and provides personalized recommendations. Furthermore, AI aids in automating the analysis of natural data, such as medical images. The presentation concludes by emphasizing the profound impact of AI on contemporary data management and knowledge utilization. 60 * науковий керівник Keywords-Artificial Intelligence, Machine Learning, Neural Networks, Data Analysis, Knowledge Utilization, Big Data, Natural Language Processing, Recommendation Systems, Computer Vision. 1. Machine Learning for Data and Knowledge Analysis Machine learning (ML) is a pivotal branch of artificial intelligence that revolutionizes the way we analyze and utilize data and knowledge. ML enables computers to learn from data and discover dependencies that may be difficult or even impossible to discern using traditional methods. It finds applications in areas such as: Prediction and Recommendations: ML models are developed to predict events, such as price changes in financial markets, and offer personalized recommendations to users, enhancing their consumer experience. Classification and Recognition: Machine learning systems can automatically classify data or recognize objects in images and videos. This has applications in fields from medicine to security. 2. Neural Networks and Deep Learning in Text and Language Processing Neural networks, particularly deep learning, serve as powerful tools for processing text and natural language. They enable the development of models that can understand and generate linguistic data [1] . Key applications of this technology include: Machine Translation: Deep learning systems allow the creation of machine translators capable of automatically translating texts between different languages with impressive accuracy. Sentiment Analysis: Neural networks can analyze textual data to determine sentiment and mood, which is crucial for marketing and brand reputation. 3. Handling Big Data with AI Database and knowledge systems deal with vast amounts of data (Big Data), and artificial intelligence significantly eases their processing and analysis. The use of AI allows for: 61 * науковий керівник Efficient Data Processing and Analysis: AI-supported database systems can rapidly and accurately analyze large datasets, identifying dependencies and patterns that aid in making more informed decisions [2] . Personalized Recommendations: Through Big D

FAQs

How does machine learning contribute to database and knowledge analysis?

Machine learning enables computers to learn from data, discover complex dependencies, and support prediction, recommendations, classification, and recognition tasks.

What role do neural networks play in text and language processing?

Neural networks and deep learning help process natural language, enabling machine translation and sentiment analysis from textual data.

How can AI assist in analyzing big datasets and providing recommendations?

AI-supported database systems can rapidly analyze large datasets to identify patterns, while AI recommendation systems use Big Data to provide personalized suggestions.

Sep 17, 2026

Upload by Ophelia