Systems and methods for personalizing search engine recall and ranking using machine learning techniques

A method implemented via execution of computing instructions configured to run at one or more processors and stored at non-transitory computer-readable media, the method comprising:

• receiving, at a search engine, a user search query submitted by a user;
• generating, using a recall personalization model, a simulated query that supplements the user search query with a feature vector reflecting personalization preferences of the user, generating, using a recall personalization model, a simulated query that supplements the user search query with a feature vector reflecting personalization preferences of the user, wherein the recall personalization model utilizes an attribute selection component associated with the feature vector;
• and the recall personalization model is a machine learning model configured to convert the user search query into the simulated query;
• and
• generating, using the search engine, search results for the user search query based, at least in part, on the simulated query that accounts for the personalization preferences of the user.