Ebay, Incorporated

Shrish Mishra

Manas Haribhai Somaiya

Rajyashree Mukherjee

Fang-Hsiang Su

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.

Method of identifying temporal demand of queries and metadata to give better autocomplete queries and improved search results

In various example embodiments, a system and method for enhancing autocomplete search suggestions are presented. The system receives a query portion with a token portion from a client device and generates a first search query suggestion set having a first order based on the token portion. The system accesses a token pool associated with the client device and generates a second search query suggestion set having a second order based on the token portion and the token pool. The system selects a first subset of search query suggestions and a second subset of search query suggestions. The system merges the first subset of search query suggestions and the second subset of search query suggestions into a third search query suggestion set, organizes the third search query suggestion set into a third order distinct from the first and second orders, and causes presentation of the third search query suggestion set.

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Mountain View, CA, United States of America

Shrish Mishra