Exploring the intersection of text mining and Ai: Methodologies, applications, and ethical considerations

Abstract

Text mining, or text analysis, involves extracting meaningful patterns and insights from unstructured text data gathered from various sources. By applying multiple Artificial Intelligence (AI) algorithms, text mining enables organizations to process this information and derive valuable insights that inform decision-making, particularly in text-intensive sectors like healthcare and law. This paper aims to provide an overview of text mining, focusing on its techniques, application domains, and the most significant challenges. The discussion centers on fundamental methods in text mining, such as natural language processing (NLP) and information extraction(IE). Additionally, the paper explores how current AI techniques are employed in these industries to enhance business processes, improving task efficiency and accuracy. It also addresses the ethical considerations associated with AI use, emphasizing the need to develop responsible AI systems that enhance decision-making and maintain user trust and confidence.