Text mining refers to extracting knowledge from unstructured text data. It is needed because most biological knowledge exists in unstructured research papers, making it difficult for scientists to manually analyze large amounts of text. Challenges include dealing with noisy, unstructured data and complex relationships between concepts. The text mining process involves preprocessing text through steps like tokenization, feature selection, and parsing to extract meaningful features before analysis can be done through classification, clustering, or other techniques. Potential applications are wide-ranging across domains like customer profiling, trend analysis, and web search.

1. Text mining: Introduction and data preparation