Machine learning enables automatic classification and tagging of text content for organizing large document collections.

Text Classification assigns predefined categories using supervised learning with labeled examples.

Feature Extraction transforms text using bag-of-words, TF-IDF, or word embeddings.

Topic Modeling discovers themes without predefined categories using techniques like LDA.

Semantic Tagging identifies entities and relations beyond keyword matching.