Reranking involves taking an initial list of results, typically from a search or retrieval process, and rearranging them based on additional factors, such as user preferences, contextual information, or relevance scoring from a model. For instance, after retrieving articles based on a search query, reranking might consider the user's previous searches to present the most pertinent articles first. This is crucial for enhancing the user experience in search engines and recommendation systems.