US Patent Issued to Maplebear on Nov. 3 for "Machine learning-based ranking of cold-start items in search systems using predicted interaction rates" (American, Canadian Inventors)

ALEXANDRIA, Va., Nov. 3 -- United States Patent no. 12,783,529, issued on Nov. 3, was assigned to Maplebear Inc. (San Francisco).

"Machine learning-based ranking of cold-start items in search systems using predicted interaction rates" was invented by Xiao Xiao (San Diego), Lee Cohn (Chicago), Taesik Na (Issaquah, Wash.), Vinesh Reddy Gudla (South San Francisco, Calif.), Tejaswi Tenneti (San Carlos, Calif.) and Quan Kong (Coquitlam, Canada).

According to the abstract* released by the U.S. Patent & Trademark Office: "An online system predicts the likelihood of user interactions with new items with little or no historic performance data by leveraging historic performance data of similar items. The online system identifies similar items by co...