Invention Grant
- Patent Title: Ranking search results using hierarchically organized machine learning based models
-
Application No.: US16708925Application Date: 2019-12-10
-
Publication No.: US11327979B2Publication Date: 2022-05-10
- Inventor: Jayesh Govindarajan , Nicholas Beng Tek Geh , Ammar Haris , Zachary Alexander , Scott Thurston Rickard, Jr. , Clifford Z. Huang
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com, inc.
- Current Assignee: salesforce.com, inc.
- Current Assignee Address: US CA San Francisco
- Agency: Fenwick & West LLP
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06F16/2457 ; G06F16/9032 ; G06F16/903 ; G06N20/00 ; G06N20/20

Abstract:
A multi-tenant system stores a hierarchy of machine-learned models, wherein each machine-learned model is configured to receive as input a set of search results and generate as output scores for ranking the set of search results. Each machine-learned model is associated with a set of dimensions. The system evaluates search query performance. Performance below a threshold causes a new model to be generated and added to the hierarchy of models. Upon execution of a new search query associated with the same set of dimensions as the newly created model, the new model is used to rank that search query's search results.
Information query