Methods Of Intellectual Analysis Of Textual Data
Keywords:
Textual Data, Intelligent Analysis, Artificial Intelligence, Machine LearningAbstract
This article examines modern methods of intellectual analysis of textual data, their theoretical foundations, and practical applications. Particular attention is given to text processing, data classification, clustering, sentiment analysis, topic modeling, and knowledge extraction using artificial intelligence and machine learning algorithms. The study highlights the role of Natural Language Processing (NLP) technologies in handling the rapidly growing volume of textual information. Various approaches to extracting meaningful insights from unstructured text are analyzed, and their effectiveness in supporting decision-making processes is evaluated. The results demonstrate the potential of intelligent text analysis methods for improving information management, knowledge discovery, and data-driven decision-making across different domains
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