Query intelligence engine

Abstract

Methods, systems, and computer storage media for providing a query management engine and a query intelligence engine in an item listing system are described. In operation, historical queries are accessed. Conceptual-category annotations are determined using a Large Language Model (LLM) based on semantic information associated with the historical queries. A concept summary comprising the conceptual-category annotations of the historical queries is generated based on the conceptual-category annotations. An aspect knowledge set is generated based on query-level matching and item-level matching that identify aspects associated with one or more items in an item listing platform. The concept summary is compared to the aspect knowledge set to generate a gap analysis output, the gap analysis output identifies one or more missing aspects associated with the aspect knowledge set of the item listing platform; and one or more missing aspects are incorporated into one or more features associated with the item listing platform.

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