Text Mining
Text mining, also known as text analytics, is the process of extracting meaningful information and insights from unstructured text data using computational techniques. It involves analyzing large volumes of text to discover patterns, trends, and relationships, often leveraging natural language processing (NLP) and machine learning. Common applications include sentiment analysis, topic modeling, and information retrieval from sources like documents, social media, or web pages.
Developers should learn text mining when working with projects that involve analyzing unstructured text data, such as building recommendation systems, chatbots, or content analysis tools. It is essential for tasks like customer feedback analysis, automated document categorization, and extracting actionable insights from textual sources in fields like marketing, healthcare, or finance. Mastery of text mining enables efficient handling of big data challenges where traditional structured data methods fall short.