Text mining software operates by converting unstructured text data into a structured format that can be analyzed. The process typically involves several steps:
Data Collection: Gathering raw text data from various sources such as journals, patents, and research papers. Pre-processing: Cleaning and organizing the text data to remove noise and irrelevant information. Text Analysis: Employing natural language processing (NLP) techniques to understand the context and semantics of the text. Pattern Recognition: Identifying patterns and trends within the text data. Data Visualization: Presenting the analyzed data in an easily interpretable format, such as graphs or charts.
