Journal of Data Mining and Knowledge Engineering ISSN: 3139-5341 (Online)

Abstract

The proliferation of digital content has created an urgent need for effective tools to process, analyze, and extract meaningful insights from vast unstructured textual data. Machine learning (ML) algorithms have emerged as a pivotal force in text mining, enabling knowledge discovery across diverse domains such as healthcare, education, finance, and social media analysis. This paper explores the applications of ML in text mining for knowledge discovery, focusing on techniques like natural language processing (NLP), deep learning, and unsupervised learning. Through the integration of original tables and 2D figures, the study delves into the methodologies, challenges, and future directions in this dynamic field.

Keywords: Machine Learning, Text Mining, Knowledge Discovery, Natural Language Processing, Deep Learning, Unsupervised Learning