Presentation of related and corrected queries for a search engine

A method comprising:

• training a machine learning model on a set of pairs, each pair comprising (i) a respective prior search query and (ii) a composite vector that describes a respective document and is responsive to the respective prior search query;
• receiving a current search query;
• converting, with the trained machine learning model, an embedded representation of the current search query into a document vector in a vector space;
• selecting one or more of the composite vectors that are within a predetermined distance of the document vector in the vector space;
• and
• generating a response to the current search query, the response comprising one or more prior search queries to which the one or more of the composite vectors were responsive.

A system comprising:

• a processor;
• and
• a memory storing instructions that, when executed by the processor, cause the system to perform a method comprising:
• training a machine learning model on a set of pairs, each pair comprising (i) a respective prior search query and (ii) a composite vector that describes a respective document and is responsive to the respective prior search query;
• receiving a current search query;
• converting, with the trained machine learning model, an embedded representation of the current search query into a document vector in a vector space;
• selecting one or more of the composite vectors that are within a predetermined distance of the document vector in the vector space;
• and
• generating a response to the current search query, the response comprising one or more prior search queries to which the one or more of the composite vectors were responsive.