{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9779087","patent":{"patent_number":"US-9779087","title":"Cross-lingual discriminative learning of sequence models with posterior regularization","assignee":null,"inventors":[],"filing_date":"2013-12-13T00:00:00.000Z","publication_date":"2017-10-03T00:00:00.000Z","cpc_codes":["G06F","G06F","G06F"],"num_claims":14,"abstract":"A computer-implemented method can include obtaining (i) an aligned bi-text for a source language and a target language, and (ii) a supervised sequence model for the source language. The method can include labeling a source side of the aligned bi-text using the supervised sequence model and projecting labels from the labeled source side to a target side of the aligned bi-text to obtain a labeled target side of the aligned bi-text. The method can include filtering the labeled target side based on a task of a natural language processing (NLP) system configured to utilize a sequence model for the target language to obtain a filtered target side of the aligned bi-text. The method can also include training the sequence model for the target language using posterior regularization with soft constraints on the filtered target side to obtain a trained sequence model for the target language."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Cross-lingual discriminative learning of sequence models with posterior regularization","description":"A computer-implemented method can include obtaining (i) an aligned bi-text for a source language and a target language, and (ii) a supervised sequence model for the source language. The method can inc","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9779087","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-9779087","citation_suggestion":"Patentable. \"Cross-lingual discriminative learning of sequence models with posterior regularization\" (US-9779087). https://patentable.app/patents/US-9779087","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9779087","json":"https://patentable.app/api/llm-context/US-9779087","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T05:17:46.791Z"}