US Patent Issued to Salesforce on May 13 for "Diversity and explainability parameters for recommendation accuracy in machine learning recommendation systems" (Singaporean, American, Irish, Indian Inventors)

ALEXANDRIA, Va., June 12 -- United States Patent no. 12,298,982, issued on May 13, was assigned to Salesforce Inc. (San Francisco).

"Diversity and explainability parameters for recommendation accuracy in machine learning recommendation systems" was invented by Wenzhuo Yang (Singapore), Jia Li (Mountain View, Calif.), Chenxi Li (Belmont, Calif.), Latrice Barnett (Oakland, Calif.), Markus Anderle (Moraga, Calif.), Simo Arajarvi (Dublin), Harshavardhan Utharavalli (Hyderabad, India), Caiming Xiong (Menlo Park, Calif.), Richard Socher (Menlo Park, Calif.) and Chu Hong Hoi (Singapore).

According to the abstract* released by the U.S. Patent & Trademark Office: "Embodiments are directed to a machine learning recommendation system. The system rec...