Embodiments describe systems and methods for identifying temporal demand for queries and using metadata to modify autocomplete results. In one embodiment, a record of historical queries is stored by a system and analyzed to identify periodic or repeated events where demand for autocomplete results associated with one or more categories deviates from normal demand. A temporal model based on this record is used to adjust autocomplete search results during subsequent time periods associated with the repeated events.