{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11977660","patent":{"patent_number":"US-11977660","title":"Machine learning modeling to identify sensitive data","assignee":null,"inventors":[],"filing_date":"2021-09-15T00:00:00.000Z","publication_date":"2024-05-07T00:00:00.000Z","cpc_codes":["G06F","G06F","G06F","G06F"],"num_claims":20,"abstract":"Methods and systems identify and redact PII. A PII sensitivity detection framework includes multiple layers where each layer corresponds to a model. The framework analyzes data stored within different data tables and predicts whether a data column includes PII. The first layer corresponds to an AI model that analyzes each column metadata and predicts a first score indicative of a first likelihood of PII existence. The second layer corresponds to a rule-based model that uses various rules to determine a second score indicative of a second likelihood of PII existence for each column. The third layer corresponds to a column content model that analyzes content of each column using various natural language processing techniques to generate a third score indicative of a third likelihood of PII existence. The framework masks data presented to a user based on the scores generated via execution of one or more of the layers."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Machine learning modeling to identify sensitive data","description":"Methods and systems identify and redact PII. A PII sensitivity detection framework includes multiple layers where each layer corresponds to a model. The framework analyzes data stored within different","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11977660","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-11977660","citation_suggestion":"Patentable. \"Machine learning modeling to identify sensitive data\" (US-11977660). https://patentable.app/patents/US-11977660","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11977660","json":"https://patentable.app/api/llm-context/US-11977660","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T03:24:03.480Z"}