{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-10540610","patent":{"patent_number":"US-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":null,"inventors":[],"filing_date":"2016-04-27T00:00:00.000Z","publication_date":"2020-01-21T00:00:00.000Z","cpc_codes":["G06N","G06N","H04L","G06N","G06N"],"num_claims":16,"abstract":"Methods, apparatus, and computer-readable media are provided for analyzing a cluster of communications, such as B2C emails, to generate a template for the cluster that defines transient segments and fixed segments of the cluster of communications. More particularly, methods, apparatus, and computer-readable media are provided for generating and/or applying a trained structured machine learning model for a generated template that can be used to determine, for one or more transient segments of subsequent communications, a corresponding probability that a given semantic label is the correct semantic label for extracted content of the transient segment(s)."},"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","description":"Methods, apparatus, and computer-readable media are provided for analyzing a cluster of communications, such as B2C emails, to generate a template for the cluster that defines transient segments and f","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-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/US-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\" (US-10540610). https://patentable.app/patents/US-10540610","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-10540610","json":"https://patentable.app/api/llm-context/US-10540610","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T03:13:43.883Z"}