Issues recommendations using machine learning

A system comprising:

• at least one data processor;
• and
• memory storing instructions which, when executed by the at least one data processor, result in operations comprising:
• receiving a query requesting issues relevant to a user;
• retrieving a plurality of issues responsive to the query;
• generating a user similarity matrix by generating a plurality of user profile vectors and calculating a similarity between each pair of user profile vectors;
• first ranking the retrieved issues using a first machine learning model to result in a first subset of the retrieved issues;
• second ranking the first subset of the retrieved issues using a second, different machine learning model to result in a second subset of the retrieved issues, the second subset of the retrieved issues being a subset of the first subset of the retrieved issues;
• and
• providing data responsive to the query comprising at least a portion of the second subset of the retrieved issues,
• wherein generating a user profile vector comprises:
• scoring each issue based on user actions stored in a user actions log;
• ranking keywords for the user based on the scoring of the issues to generate a list of top keywords;
• and
• generating user keywords vectors based on the list of top keywords.

A non-transitory computer program product storing instructions which, when executed by at least one computing device, results in operations comprising:

• receiving a query requesting issues relevant to a user;
• retrieving a plurality of issues responsive to the query;
• generating a user similarity matrix by generating a plurality of user profile vectors and calculating a similarity between each pair of user profile vectors;
• first ranking the retrieved issues using a first machine learning model to result in a first subset of the retrieved issues;
• second ranking the first subset of the retrieved issues using a second, different machine learning model to result in a second subset of the retrieved issues, the second subset of the retrieved issues being a subset of the first subset of the retrieved issues;
• and
• providing data responsive to the query comprising at least a portion of the second subset of the retrieved issues,
• wherein generating a user profile vector comprises:
• scoring each issue based on user actions stored in a user actions log;
• ranking keywords for the user based on the scoring of the issues to generate a list of top keywords;
• and
• generating user keywords vectors based on the list of top keywords.