For example, a user may be searching for cheap headphones, but through a combination of misspellings and typos their final query may be “chep head phones”. Rather than make one guess at a correction, spelling correction will search for a variety of different queries depending on the edit distance, term popularity, and phrase correction. The final weighted query that is sent to the engine for processing may look like: