ADVANCES IN ARTIFICIAL INTELLIGENCE FOR ANALYSIS AND UNDERSTANDING OF DOCUMENT: A COMPREHENSIVE REVIEW

Abstract

This scientific review examines advancements in applying artificial intelligence (AI) to document processing and understanding. The study highlights key methods and technologies, including text recognition, document categorization, data extraction, and semantic interpretation are covered. These methods tackle the increasing demand for processing and understanding extensive textual information in the modern data-centric world. The paper examines the creation of optimized algorithms for digitizing text, organizing content into categories, retrieving structured data, and producing brief summaries from the given material. Moreover, the article highlights the importance of leveraging deep learning and natural language processing (NLP) methods to enhance the precision and comprehensiveness of document analysis.

Significant challenges, like the complexity of language interpretation and limitations of current AI systems in handling diverse contexts, are overviewed. The ethical implications of AI, including concerns around data privacy, bias, and societal impact, are also examined. The review identifies practical applications across various fields, including sociology, marketing, healthcare, and education, showcasing AI's transformative potential for automating processes like sentiment analysis, named entity recognition, and real-time information monitoring.

The paper concludes by highlighting potential avenues for future exploration, such as improving real-time performance, developing versatile software for text processing, and implementing intuitive interfaces to make AI-driven tools more accessible to a broader audience. By addressing these challenges, AI technologies can significantly advance the efficiency and effectiveness of document processing, offering substantial benefits to scientific research, business operations, public services, and more.