Text ranking is a method used in information retrieval and natural language processing to evaluate and organize text based on its relevance to a specific query. It involves assigning scores to documents or sentences, allowing systems to determine which pieces of text are most pertinent to the user's needs. This process is essential for search engines and recommendation systems, helping users find the most useful information quickly. The ranking process often utilizes algorithms that analyze various factors, such as keyword frequency, context, and user behavior. Techniques like TF-IDF (Term Frequency-Inverse Document Frequency) and PageRank are commonly employed to enhance the accuracy of the results, ensuring that the most relevant content is presented first.