{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/10540610","patent":{"patent_number":"10540610","title":"GENERATING AND APPLYING A TRAINED STRUCTURED MACHINE LEARNING MODEL FOR DETERMINING A SEMANTIC LABEL FOR CONTENT OF A TRANSIENT SEGMENT OF A COMMUNICATION","assignee":"Unknown","inventors":["Jie Yang","Amr Ahmed","Luis Garcia Pueyo","Mike Bendersky","Amitabh Saikia","Marc-Allen Cartright","Marc Alexander Najork","MyLinh Yang","Hui Tan","Weinan Zhang","Vanja Josifovski","Alexander J. Smola"],"filing_date":null,"publication_date":"2020-01-21T00:00:00.000Z","cpc_codes":[],"num_claims":null,"abstract":null},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"GENERATING AND APPLYING A TRAINED STRUCTURED MACHINE LEARNING MODEL FOR DETERMINING A SEMANTIC LABEL FOR CONTENT OF A TRANSIENT SEGMENT OF A COMMUNICATION","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/10540610","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/10540610","citation_suggestion":"Patentable. \"GENERATING AND APPLYING A TRAINED STRUCTURED MACHINE LEARNING MODEL FOR DETERMINING A SEMANTIC LABEL FOR CONTENT OF A TRANSIENT SEGMENT OF A COMMUNICATION\" (10540610). https://patentable.app/patents/10540610","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/10540610","json":"https://patentable.app/api/llm-context/10540610","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T12:22:29.923Z"}