|Description||Microsoft 2006 - A method and system for learning a ranking function that uses a normalized, query-level error function is provided. A ranking system learns a ranking function using training data that includes, for each query, the corresponding documents and, for each document, its relevance to the corresponding query. The ranking system uses an error calculation algorithm that calculates an error between the actual relevances and the calculated relevances for the documents of each query. The ranking system normalizes the errors so that the total errors for each query will be weighted equally. The ranking system then uses the normalized error to learn a ranking function that works well for both queries with many documents in their search results and queries with few documents in their search results.